Achieving a ‘single version of the truth’ is critical to any MDM, DW, or data integration initiative. But have you ever tried to get people to agree on a single definition of “customer”? Or to get Sales, Marketing, and IT to agree on a target audience?
This webinar will discuss how a conceptual data model can be used as a powerful communication tool for data-intensive initiatives. It will cover how to build a high-level data model, how the core concepts in a data model can have significant business impact on an organization, and will provide some easy-to-use templates and guidelines for a step-by-step approach to implementing a conceptual data model in your organization.
Data Modelling 101 half day workshop presented by Chris Bradley at the Enterprise Data and Business Intelligence conference London on November 3rd 2014.
Chris Bradley is a leading independent information strategist.
Contact chris.bradley@dmadvisors.co.uk
Gartner: Master Data Management FunctionalityGartner
Gartner will further examine key trends shaping the future MDM market during the Gartner MDM Summit 2011, 2-3 February in London. More information at www.europe.gartner.com/mdm
This introduction to data governance presentation covers the inter-related DM foundational disciplines (Data Integration / DWH, Business Intelligence and Data Governance). Some of the pitfalls and success factors for data governance.
• IM Foundational Disciplines
• Cross-functional Workflow Exchange
• Key Objectives of the Data Governance Framework
• Components of a Data Governance Framework
• Key Roles in Data Governance
• Data Governance Committee (DGC)
• 4 Data Governance Policy Areas
• 3 Challenges to Implementing Data Governance
• Data Governance Success Factors
To take a “ready, aim, fire” tactic to implement Data Governance, many organizations assess themselves against industry best practices. The process is not difficult or time-consuming and can directly assure that your activities target your specific needs. Best practices are always a strong place to start.
Join Bob Seiner for this popular RWDG topic, where he will provide the information you need to set your program in the best possible direction. Bob will walk you through the steps of conducting an assessment and share with you a set of typical results from taking this action. You may be surprised at how easy it is to organize the assessment and may hear results that stimulate the actions that you need to take.
In this webinar, Bob will share:
- The value of performing a Data Governance best practice assessment
- A practical list of industry Data Governance best practices
- Criteria to determine if a practice is best practice
- Steps to follow to complete an assessment
- Typical recommendations and actions that result from an assessment
LDM Webinar: Data Modeling & Business IntelligenceDATAVERSITY
Business Intelligence (BI) is a valuable way to use information to show the overall health and performance of the organization. At its core is quality, well-structured data that allows for successful reporting and analytics. A data model helps provide both the business definitions as well as the structural optimization needed for successful BI implementations.
Join this webinar to see how a data model underpins business intelligence and analytics in today’s organization.
Data modelling for the business half day workshop presented at the Enterprise Data & Business Intelligence conference in London on November 3rd 2014
chris.bradley@dmadvisors.co.uk
Data Modelling 101 half day workshop presented by Chris Bradley at the Enterprise Data and Business Intelligence conference London on November 3rd 2014.
Chris Bradley is a leading independent information strategist.
Contact chris.bradley@dmadvisors.co.uk
Gartner: Master Data Management FunctionalityGartner
Gartner will further examine key trends shaping the future MDM market during the Gartner MDM Summit 2011, 2-3 February in London. More information at www.europe.gartner.com/mdm
This introduction to data governance presentation covers the inter-related DM foundational disciplines (Data Integration / DWH, Business Intelligence and Data Governance). Some of the pitfalls and success factors for data governance.
• IM Foundational Disciplines
• Cross-functional Workflow Exchange
• Key Objectives of the Data Governance Framework
• Components of a Data Governance Framework
• Key Roles in Data Governance
• Data Governance Committee (DGC)
• 4 Data Governance Policy Areas
• 3 Challenges to Implementing Data Governance
• Data Governance Success Factors
To take a “ready, aim, fire” tactic to implement Data Governance, many organizations assess themselves against industry best practices. The process is not difficult or time-consuming and can directly assure that your activities target your specific needs. Best practices are always a strong place to start.
Join Bob Seiner for this popular RWDG topic, where he will provide the information you need to set your program in the best possible direction. Bob will walk you through the steps of conducting an assessment and share with you a set of typical results from taking this action. You may be surprised at how easy it is to organize the assessment and may hear results that stimulate the actions that you need to take.
In this webinar, Bob will share:
- The value of performing a Data Governance best practice assessment
- A practical list of industry Data Governance best practices
- Criteria to determine if a practice is best practice
- Steps to follow to complete an assessment
- Typical recommendations and actions that result from an assessment
LDM Webinar: Data Modeling & Business IntelligenceDATAVERSITY
Business Intelligence (BI) is a valuable way to use information to show the overall health and performance of the organization. At its core is quality, well-structured data that allows for successful reporting and analytics. A data model helps provide both the business definitions as well as the structural optimization needed for successful BI implementations.
Join this webinar to see how a data model underpins business intelligence and analytics in today’s organization.
Data modelling for the business half day workshop presented at the Enterprise Data & Business Intelligence conference in London on November 3rd 2014
chris.bradley@dmadvisors.co.uk
How to Build & Sustain a Data Governance Operating Model DATUM LLC
Learn how to execute a data governance strategy through creation of a successful business case and operating model.
Originally presented to an audience of 400+ at the Master Data Management & Data Governance Summit.
Visit www.datumstrategy.com for more!
Describes what Enterprise Data Architecture in a Software Development Organization should cover and does that by listing over 200 data architecture related deliverables an Enterprise Data Architect should remember to evangelize.
Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how Data Architecture is a key component of an overall Enterprise Architecture for enhanced business value and success.
Data Catalog for Better Data Discovery and GovernanceDenodo
Watch full webinar here: https://buff.ly/2Vq9FR0
Data catalogs are en vogue answering critical data governance questions like “Where all does my data reside?” “What other entities are associated with my data?” “What are the definitions of the data fields?” and “Who accesses the data?” Data catalogs maintain the necessary business metadata to answer these questions and many more. But that’s not enough. For it to be useful, data catalogs need to deliver these answers to the business users right within the applications they use.
In this session, you will learn:
*How data catalogs enable enterprise-wide data governance regimes
*What key capability requirements should you expect in data catalogs
*How data virtualization combines dynamic data catalogs with delivery
Data Integration is a key part of many of today’s data management challenges: from data warehousing, to MDM, to mergers & acquisitions. Issues can arise not only in trying to align technical formats from various databases and legacy systems, but in trying to achieve common business definitions and rules.
Join this webinar to see how a data model can help with both of these challenges – from ‘bottom-up’ technical integration, to the ‘top-down’ business alignment.
Data modelling has been around since the mid 1970's but in many organisations there is considerable scepticism and downright distrust regarding the place dta modelling should occupy. So why does data modelling still have to be "sold" in many companies, and in others people simply don't believe it's necessary " the software package has all I need"! This paper looks at the failure of organisations to capitalise on the benefits data modelling can yield and examines where in the changing information systems landscape modelling is relevant.
Reference data is something we often encounter in our projects. In our experience, it is often underestimated and does not get enough attention. In the webinar, we want to make you aware of some interesting aspects of ‘reference data’ such as how it relates to MDM, which it’s often mixed with.
Master Data Management – Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as customers, products, vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar will provide practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
DAS Slides: Building a Data Strategy — Practical Steps for Aligning with Busi...DATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task. The opportunity in getting it right can be significant, however, as data drives many of the key initiatives in today’s marketplace from digital transformation, to marketing, to customer centricity, population health, and more. This webinar will help de-mystify data strategy and data architecture and will provide concrete, practical ways to get started.
DAS Slides: Data Governance - Combining Data Management with Organizational ...DATAVERSITY
Data Governance is both a technical and an organizational discipline, and getting Data Governance right requires a combination of Data Management fundamentals aligned with organizational change and stakeholder buy-in. Join Nigel Turner and Donna Burbank as they provide an architecture-based approach to aligning business motivation, organizational change, Metadata Management, Data Architecture and more in a concrete, practical way to achieve success in your organization.
Using a Semantic and Graph-based Data Catalog in a Modern Data FabricCambridge Semantics
Watch this webinar to learn about the benefits of using semantic and graph database technology to create a Data Catalog of all of an enterprise's data, regardless of source or format, as part of a modern IT or data management stack and an important step toward building an Enterprise Data Fabric.
Data protection and privacy regulations such as the EU’s General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and Singapore’s Personal Data Protection Act (PDPA) have been major drivers for data governance initiatives and the emergence of data catalog solutions. Organizations have an ever-increasing appetite to leverage their data for business advantage, either through internal collaboration, data sharing across ecosystems, direct commercialization, or as the basis for AI-driven business decision-making. This requires data governance and especially data asset catalog solutions to step up once again and enable data-driven businesses to leverage their data responsibly, ethically, compliantly, and accountably.
This presentation explores how data catalog has become a key technology enabler in overcoming these challenges.
Data Profiling, Data Catalogs and Metadata HarmonisationAlan McSweeney
These notes discuss the related topics of Data Profiling, Data Catalogs and Metadata Harmonisation. It describes a detailed structure for data profiling activities. It identifies various open source and commercial tools and data profiling algorithms. Data profiling is a necessary pre-requisite activity in order to construct a data catalog. A data catalog makes an organisation’s data more discoverable. The data collected during data profiling forms the metadata contained in the data catalog. This assists with ensuring data quality. It is also a necessary activity for Master Data Management initiatives. These notes describe a metadata structure and provide details on metadata standards and sources.
This presentation was part of the IDS Webinar on Data Governance. It gives a brief overview of the history on Data Governance, describes how governing data has to be further developed in the era of business and data ecosystems, and outlines the contribution of the International Data Spaces Association on the topic.
Reference matter data management:
Two categories of structured data :
Master data: is data associated with core business entities such as customer, product, asset, etc.
Transaction data: is the recording of business transactions such as orders in manufacturing, loan and credit card payments in banking, and product sales in retail.
Reference data: is any kind of data that is used solely to categorize other data found in a database, or solely for relating data in a database to information beyond the boundaries of the enterprise .
Lessons in Data Modeling: Why a Data Model is an Important Part of Your Data ...DATAVERSITY
Data can provide tremendous value to an organization in today’s information-driven economy. New customer insights, better efficiency, and new product innovation are just some of the ways organizations are obtaining value through data. But in order to achieve this value, a strong data architecture is required to ensure that the data infrastructure runs smoothly, while at the same time aligning with business needs and corporate culture. A Data Strategy can assist in building a data architecture foundation through:
Identifying business requirements, rules & definitions via a business-centric data model
Creating a data inventory & integrating disparate data sources
Building a technical data architecture through data models & related artifacts
Coordinating the people, processes and culture necessary for success
Identifying tools & technology needed for creating & maintaining high quality data
RWDG Slides: Apply Data Governance to Agile EffortsDATAVERSITY
Data Governance Programs and Agile Data Projects are known to conflict when it comes to how the information and data is managed. Senior leadership has come to expect both the formal governance of data and data projects to be delivered quickly and effectively. These two requirements continue to cause problems.
Bob Seiner will discuss how to govern data during Agile projects during this month’s installment of the RWDG webinar series. It is inevitable that governance and Agile need to work together and complement each discipline’s intended results. Bob will share several considerations for bringing the two together.
During this webinar Bob will discuss:
- Looking for common ground to stand on
- The data goals of an Agile effort
- The Agile goals of a Data Governance program
- Bridging the gap and building understanding
- Steps to apply governance to Agile efforts
RWDG Webinar: The New Non-Invasive Data Governance FrameworkDATAVERSITY
Non-Invasive Data Governance is summarized as the practice of formalizing accountability for data and the application of governance to process. Non-Invasive Data Governance describes how data governance is applied to the organization rather than being forced into the environment. A NIDG framework will be introduced in this webinar.
In this month’s installment of the RWDG webinar series, Bob Seiner will present a new data governance framework that addresses the core components of data governance for each level of the organization. The resulting framework can be used for all approaches to data governance.
In this webinar Bob will discuss:
- The five core components of a data governance effort
- The five levels where the core components will be addressed
- Detailed explanation of each component for each level
- A diagram to complete the framework for your organization
- A framework comparison across approaches
How to Build & Sustain a Data Governance Operating Model DATUM LLC
Learn how to execute a data governance strategy through creation of a successful business case and operating model.
Originally presented to an audience of 400+ at the Master Data Management & Data Governance Summit.
Visit www.datumstrategy.com for more!
Describes what Enterprise Data Architecture in a Software Development Organization should cover and does that by listing over 200 data architecture related deliverables an Enterprise Data Architect should remember to evangelize.
Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how Data Architecture is a key component of an overall Enterprise Architecture for enhanced business value and success.
Data Catalog for Better Data Discovery and GovernanceDenodo
Watch full webinar here: https://buff.ly/2Vq9FR0
Data catalogs are en vogue answering critical data governance questions like “Where all does my data reside?” “What other entities are associated with my data?” “What are the definitions of the data fields?” and “Who accesses the data?” Data catalogs maintain the necessary business metadata to answer these questions and many more. But that’s not enough. For it to be useful, data catalogs need to deliver these answers to the business users right within the applications they use.
In this session, you will learn:
*How data catalogs enable enterprise-wide data governance regimes
*What key capability requirements should you expect in data catalogs
*How data virtualization combines dynamic data catalogs with delivery
Data Integration is a key part of many of today’s data management challenges: from data warehousing, to MDM, to mergers & acquisitions. Issues can arise not only in trying to align technical formats from various databases and legacy systems, but in trying to achieve common business definitions and rules.
Join this webinar to see how a data model can help with both of these challenges – from ‘bottom-up’ technical integration, to the ‘top-down’ business alignment.
Data modelling has been around since the mid 1970's but in many organisations there is considerable scepticism and downright distrust regarding the place dta modelling should occupy. So why does data modelling still have to be "sold" in many companies, and in others people simply don't believe it's necessary " the software package has all I need"! This paper looks at the failure of organisations to capitalise on the benefits data modelling can yield and examines where in the changing information systems landscape modelling is relevant.
Reference data is something we often encounter in our projects. In our experience, it is often underestimated and does not get enough attention. In the webinar, we want to make you aware of some interesting aspects of ‘reference data’ such as how it relates to MDM, which it’s often mixed with.
Master Data Management – Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as customers, products, vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar will provide practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
DAS Slides: Building a Data Strategy — Practical Steps for Aligning with Busi...DATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task. The opportunity in getting it right can be significant, however, as data drives many of the key initiatives in today’s marketplace from digital transformation, to marketing, to customer centricity, population health, and more. This webinar will help de-mystify data strategy and data architecture and will provide concrete, practical ways to get started.
DAS Slides: Data Governance - Combining Data Management with Organizational ...DATAVERSITY
Data Governance is both a technical and an organizational discipline, and getting Data Governance right requires a combination of Data Management fundamentals aligned with organizational change and stakeholder buy-in. Join Nigel Turner and Donna Burbank as they provide an architecture-based approach to aligning business motivation, organizational change, Metadata Management, Data Architecture and more in a concrete, practical way to achieve success in your organization.
Using a Semantic and Graph-based Data Catalog in a Modern Data FabricCambridge Semantics
Watch this webinar to learn about the benefits of using semantic and graph database technology to create a Data Catalog of all of an enterprise's data, regardless of source or format, as part of a modern IT or data management stack and an important step toward building an Enterprise Data Fabric.
Data protection and privacy regulations such as the EU’s General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and Singapore’s Personal Data Protection Act (PDPA) have been major drivers for data governance initiatives and the emergence of data catalog solutions. Organizations have an ever-increasing appetite to leverage their data for business advantage, either through internal collaboration, data sharing across ecosystems, direct commercialization, or as the basis for AI-driven business decision-making. This requires data governance and especially data asset catalog solutions to step up once again and enable data-driven businesses to leverage their data responsibly, ethically, compliantly, and accountably.
This presentation explores how data catalog has become a key technology enabler in overcoming these challenges.
Data Profiling, Data Catalogs and Metadata HarmonisationAlan McSweeney
These notes discuss the related topics of Data Profiling, Data Catalogs and Metadata Harmonisation. It describes a detailed structure for data profiling activities. It identifies various open source and commercial tools and data profiling algorithms. Data profiling is a necessary pre-requisite activity in order to construct a data catalog. A data catalog makes an organisation’s data more discoverable. The data collected during data profiling forms the metadata contained in the data catalog. This assists with ensuring data quality. It is also a necessary activity for Master Data Management initiatives. These notes describe a metadata structure and provide details on metadata standards and sources.
This presentation was part of the IDS Webinar on Data Governance. It gives a brief overview of the history on Data Governance, describes how governing data has to be further developed in the era of business and data ecosystems, and outlines the contribution of the International Data Spaces Association on the topic.
Reference matter data management:
Two categories of structured data :
Master data: is data associated with core business entities such as customer, product, asset, etc.
Transaction data: is the recording of business transactions such as orders in manufacturing, loan and credit card payments in banking, and product sales in retail.
Reference data: is any kind of data that is used solely to categorize other data found in a database, or solely for relating data in a database to information beyond the boundaries of the enterprise .
Lessons in Data Modeling: Why a Data Model is an Important Part of Your Data ...DATAVERSITY
Data can provide tremendous value to an organization in today’s information-driven economy. New customer insights, better efficiency, and new product innovation are just some of the ways organizations are obtaining value through data. But in order to achieve this value, a strong data architecture is required to ensure that the data infrastructure runs smoothly, while at the same time aligning with business needs and corporate culture. A Data Strategy can assist in building a data architecture foundation through:
Identifying business requirements, rules & definitions via a business-centric data model
Creating a data inventory & integrating disparate data sources
Building a technical data architecture through data models & related artifacts
Coordinating the people, processes and culture necessary for success
Identifying tools & technology needed for creating & maintaining high quality data
RWDG Slides: Apply Data Governance to Agile EffortsDATAVERSITY
Data Governance Programs and Agile Data Projects are known to conflict when it comes to how the information and data is managed. Senior leadership has come to expect both the formal governance of data and data projects to be delivered quickly and effectively. These two requirements continue to cause problems.
Bob Seiner will discuss how to govern data during Agile projects during this month’s installment of the RWDG webinar series. It is inevitable that governance and Agile need to work together and complement each discipline’s intended results. Bob will share several considerations for bringing the two together.
During this webinar Bob will discuss:
- Looking for common ground to stand on
- The data goals of an Agile effort
- The Agile goals of a Data Governance program
- Bridging the gap and building understanding
- Steps to apply governance to Agile efforts
RWDG Webinar: The New Non-Invasive Data Governance FrameworkDATAVERSITY
Non-Invasive Data Governance is summarized as the practice of formalizing accountability for data and the application of governance to process. Non-Invasive Data Governance describes how data governance is applied to the organization rather than being forced into the environment. A NIDG framework will be introduced in this webinar.
In this month’s installment of the RWDG webinar series, Bob Seiner will present a new data governance framework that addresses the core components of data governance for each level of the organization. The resulting framework can be used for all approaches to data governance.
In this webinar Bob will discuss:
- The five core components of a data governance effort
- The five levels where the core components will be addressed
- Detailed explanation of each component for each level
- A diagram to complete the framework for your organization
- A framework comparison across approaches
IT + Line of Business - Driving Faster, Deeper Insights TogetherDATAVERSITY
Marketo helps customers master the science of digital marketing with the analytics it provides customers. Internally, Marketo found itself afflicted with “Excel mania” and suffering from the side effects that come with it, including slow time to insights and hours lost on mundane but critical data prep. This quickly changed when they bet their BI strategy on Alteryx, Amazon Web Services (AWS), and Tableau.
Join us and hear from Tim Chandler, head of BI and data solutions, and learn how:
the stack is enabling more efficient analytics processes, as well as providing governance and scalability
IT and line of business (LOB) are effectively working together to uncover more insights, faster – saving time and resources in the process
an enterprise-class data architecture is driving business engagement and dashboard adoption across the entire company
Register now to learn how you can improve your analytics processes - leading to faster, deeper insights.
Data-Ed Slides: Data Architecture Strategies - Constructing Your Data GardenDATAVERSITY
Data architecture is foundational to an information-based operational environment. Without proper structure and efficiency in organization, data assets cannot be utilized to their full potential, which in turn harms bottom-line business value. When designed well and used effectively, however, a strong data architecture can be referenced to inform, clarify, understand, and resolve aspects of a variety of business problems commonly encountered in organizations.
The goal of this webinar is not to instruct you in being an outright data architect, but rather to enable you to envision a number of uses for data architectures that will maximize your organization’s competitive advantage.
With that being said, we will:
- Discuss data architecture’s guiding principles and best practices
- Demonstrate how to utilize data architecture to address a broad variety of organizational challenges and support your overall business strategy
- Illustrate how best to understand foundational data architecture concepts based on the DAMA International Guide to Data Management Body of Knowledge (DAMA DMBOK)
The Importance of MDM - Eternal Management of the Data MindDATAVERSITY
Despite its immaterial nature, data has a tendency to pile up as time goes on, and can quickly be rendered unusable or obsolete without careful maintenance and streamlining of processes for its management. This presentation will provide you with an understanding of reference and master data management (MDM), one such method for keeping mass amounts of business data organized and functional towards achieving business goals.
MDM’s guiding principles include the establishment and implementation of authoritative data sources and effective means of delivering data to various business processes, as well as increases to the quality of information used in organizational analytical functions (such as BI).
To that end, attendees of this webinar will learn how to:
- Structure their data management processes around these principles
- Incorporate data quality engineering into the planning of reference and MDM
- Understand why MDM is so critical to their organization’s overall data strategy
LDM Slides: How Data Modeling Fits into an Overall Enterprise ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as it relates to data and its business impact across the organization.
Join this webinar for a discussion on how a data model can be combined with an overall enterprise architecture for enhanced business value and success.
Smart Data Slides: Data Science and Business Analysis - A Look at Best Practi...DATAVERSITY
Google “citizen data scientist” today and you will see about 1M results. That number is data. It may be interesting, but it is meaningless without context. Sometimes it appears that we are drowning in data from systems and sensors but starving for insights. We definitely produce more of the former than the latter, which has created demand for more powerful tools to simplify the process and lower the skills requirement for analysis. As vendors build systems to meet this demand, we hear about the coming ”democratization” of big data as more people at varying levels within organizations are empowered to find meaning and improve their own performance with data-driven insights. This is a good thing, but it does require caution.
To paraphrase Col Jessup in A Few Good Men: You want answers? You can’t handle the data.
In this webinar, we will survey emerging approaches to simplifying analysis, and discuss the benefits, dangers, and skills required for individuals and organizations to thrive in the brave new world of analytics everywhere, for everyone.
Focus on Your Analysis, Not Your SQL CodeDATAVERSITY
Analysts in the line of business deal with a myriad of time-consuming data preparation and analytic challenges that often require IT or DBA intervention to deliver a requested dataset. Others have taught themselves “enough SQL to be dangerous”, learning the necessary code to extract the data needed to answer their business question. Self-service data analytics empowers these business analysts to take control of the entire analytics process, delivering the necessary results for better business decisions.
Join us to learn how self-service data analytics allows analysts to:
- Utilize a drag-and-drop workflow for data and analytic processes without writing code
- Minimize data movement and ensure data integrity through in-database capabilities
- Easily work across relational and non-relational databases to deliver faster business results
Self-service data analytics delivers a repeatable process that is transparent to not only business analysts, but also SQL coders and decision makers across the organization.
Yosemite Project - Part 3 - Transformations for Integrating VA data with FHIR...DATAVERSITY
In our series on The Yosemite Project, we explore RDF as a data standard for health data. In this installment, we will hear from Rafael Richards, Physician Informatician, Office of Informatics and Analytics in the Veterans Health Administration (VHA), about “Transformations for Integrating VA data with FHIR in RDF.”
The VistA EHR has its own data model and vocabularies for representing healthcare data. This webinar describes how SPARQL Inference Notation (SPIN) can be used to translate VistA data to the data represented used by FHIR, an emerging interchange standard.
WEBINAR: The Yosemite Project: An RDF Roadmap for Healthcare Information Inte...DATAVERSITY
Interoperability of electronic healthcare information remains an enormous challenge in spite of 100+ available healthcare information standards. This webinar explains the Yosemite Project, whose mission is to achieve semantic interoperability of all structured healthcare information through RDF as a common semantic foundation. It explains the rationale and technical strategy of the Yosemite Project, and describes how RDF and related standards address a two-pronged strategy for semantic interoperability: facilitating collaborative standards convergence whenever possible, and crowd-sourced data translations when necessary.
In our series on The Yosemite Project, we explore RDF as a data standard for health data. In this presentation, we will discuss with Claude Nanjo, a Software Architect at Cognitive Medical Systems, ways to expose clinical knowledge as OWL and RDF resources on the Web in order to promote greater convergence in the representation of health knowledge in the longer term. We will also explore how one might rally and coordinate the community to seed the Web with a core set of high-value resources and technologies that could greatly enhance health interoperability.
Our speaker, Joshua Mandel, will provide a lightning tour of Fast Healthcare Interoperability Resources (FHIR), an emerging clinical data standard, with a focus on its resource-oriented approach, and a discussion of how FHIR intersects with the Semantic Web. We'll look at how FHIR represents links between entities; how FHIR represents concepts from standards-based vocabularies; and how a set of FHIR instance data can be represented in RDF.
Using Semantic Technology to Drive Agile Analytics - SLIDESDATAVERSITY
How do you accelerate data warehousing to meet the demands of the data-driven economy? Semantic technology provides an agile platform to bring data together, focus on data that matters and ultimately derive a target data model that can be easily extended. This webinar will present a semantically-based data federation case study and highlight the semantic components that facilitate agile data federation in the enterprise.
WEBINAR: The Yosemite Project PART 6 -- Data-Driven Biomedical Research with ...DATAVERSITY
In this presentation, our speaker, Dr. Michel Dumontier, will explore the use of Semantic Web technologies to reduce the overwhelming burden of integrating clinical data with public biomedical data, and enabling a new generation of translational research and their clinical application.
Enterprise Data World: Data Governance - The Four Critical Success FactorsDATAVERSITY
Let’s face it, developing and implementing an Enterprise Data Governance program can be very frustrating. Issues can pop up quite unexpectedly. Support ebbs and flows for seemingly illogical reasons. And, acceptance and adoption seem to be hit or miss. So, how can practitioners ensure their program will be as successful as possible?
This webinar is designed to help practitioners understand the Four Critical Success Factors necessary for developing and sustaining an effective Data Governance program, as identified by Joy Medved based on her 20+ years as an international data consultant. Joy will provide an overview of the Four Critical Success Factors, as well as share Common Program Barriers she has experienced that lead to success breakdown. Joy will also help practitioners learn how to identify if one or more of these critical success factors is plaguing your program, and which barriers might be at fault. Rounding out the topic, Joy will share her Key Program Components, designed to help ensure successful Data Governance development and implementation.
Some of the topics discussed in this webinar include:
The Four Critical Success Factors for developing and implementing a DG program
Common Program Barriers that may be hampering your ability to drive a successful program
How to identify which barriers might be plaguing your program efforts
Key Program Components to help ensure a successful DG program
EDW Webinar: Managing Change for Successful Data GovernanceDATAVERSITY
Having trouble making your information management (IM)/data governance (DG) changes stick? How many times have you gone through this process?
Successful data governance means changes to your information management culture. Changing that culture means that you are asking people to think and behave differently about how data is created, accessed and used. If the results are to be sustainable, successful IM/DG change requires an organized and systematic way to manage those changes.
In preparation for their EDW15 tutorial, Kelle O’Neal and Pam Thomas will discuss the most significant obstacles to successful IM/DG change, and the key factors to working through those obstacles to achieve business benefit.
The Evolving Role of the Data Architect – What Does It Mean for Your Career?DATAVERSITY
If you’re a data architect, you’ve heard it all—from ‘data management is the sexiest job of the 21st century’ to ‘data management is dead’. The truth almost certainly lies somewhere in the middle of the extremes, but how can you make sense of the true future of the data architect’s role in the rapidly-changing data landscape? The Data Architect holds a unique position as the translator between business value and technical implementation.
Join this webinar to learn how you can take advantage of the uniqueness of this role to catapult your career to the next level.
The Business Value of Metadata for Data GovernanceRoland Bullivant
In today’s digital economy, data drives the core processes that deliver profitability and growth - from marketing, to finance, to sales, supply chain, and more. It is also likely that for many large organizations much of their key data is retained in application packages from SAP, Oracle, Microsoft, Salesforce and others. In order to ensure that their foundational data infrastructure runs smoothly, most organizations have adopted a data governance initiative. These typically focus on the people and processes around managing data and information. Without an actionable link to the physical systems that run key business processes, however, governance programs can often lack the ‘teeth’ to effectively implement business change.
Metadata management is a process that can link business processes and drivers with the technical applications that support them. This makes data governance actionable and relevant in today’s fast-paced and results-driven business environment. One of the challenges facing data governance teams however, is the variety in format, accessibility and complexity of metadata across the organization’s systems.
Data Architecture Strategies: Building an Enterprise Data Strategy – Where to...DATAVERSITY
The majority of successful organizations in today’s economy are data-driven, and innovative companies are looking at new ways to leverage data and information for strategic advantage. While the opportunities are vast, and the value has clearly been shown across a number of industries in using data to strategic advantage, the choices in technology can be overwhelming. From Big Data to Artificial Intelligence to Data Lakes and Warehouses, the industry is continually evolving to provide new and exciting technological solutions.
This webinar will help make sense of the various data architectures & technologies available, and how to leverage them for business value and success. A practical framework will be provided to generate “quick wins” for your organization, while at the same time building towards a longer-term sustainable architecture. Case studies will also be provided to show how successful organizations have successfully built a data strategies to support their business goals.
Data Modeling, Data Governance, & Data QualityDATAVERSITY
Data Governance is often referred to as the people, processes, and policies around data and information, and these aspects are critical to the success of any data governance implementation. But just as critical is the technical infrastructure that supports the diverse data environments that run the business. Data models can be the critical link between business definitions and rules and the technical data systems that support them. Without the valuable metadata these models provide, data governance often lacks the “teeth” to be applied in operational and reporting systems.
Join Donna Burbank and her guest, Nigel Turner, as they discuss how data models & metadata-driven data governance can be applied in your organization in order to achieve improved data quality.
Metadata management is critical for organizations looking to understand the context, definition and lineage of key data assets. Data models play a key role in metadata management, as many of the key structural and business definitions are stored within the models themselves. Can data models replace traditional metadata solutions? Or should they integrate with larger metadata management tools & initiatives?
Join this webinar to discuss opportunities and challenges around:
How data modeling fits within a larger metadata management landscape
When can data modeling provide “just enough” metadata management
Key data modeling artifacts for metadata
Organization, Roles & Implementation Considerations
Data Modeling Best Practices - Business & Technical ApproachesDATAVERSITY
Data Modeling is hotter than ever, according to a number of recent surveys. Part of the appeal of data models lies in their ability to translate complex data concepts in an intuitive, visual way to both business and technical stakeholders. This webinar provides real-world best practices in using Data Modeling for both business and technical teams.
Self-Service Data Analysis, Data Wrangling, Data Munging, and Data Modeling –...DATAVERSITY
Self-Service data analysis holds the promise of more rapid time-to-value for both business and IT users as advanced tooling & visualization helps make sense of raw and source data sets. Does this mean that the paradigm of ‘design-then-build’ that’s typical of data modeling is no longer relevant? Or is it more relevant than ever, as more eyes on the data means more questions about core business definitions.
Join Donna Burbank for this webinar to discuss the realities of where data modeling fits in this new paradigm.
DAS Slides: Building a Data Strategy – Practical Steps for Aligning with Busi...DATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task. The opportunity in getting it right can be significant, however, as data drives many of the key initiatives in today’s marketplace from digital transformation, to marketing, to customer centricity, population health, and more. This webinar will help de-mystify data strategy and data architecture and will provide concrete, practical ways to get started.
Improving Data Literacy Around Data ArchitectureDATAVERSITY
Data Literacy is an increasing concern, as organizations look to become more data-driven. As the rise of the citizen data scientist and self-service data analytics becomes increasingly common, the need for business users to understand core Data Management fundamentals is more important than ever. At the same time, technical roles need a strong foundation in Data Architecture principles and best practices. Join this webinar to understand the key components of Data Literacy, and practical ways to implement a Data Literacy program in your organization.
Data modeling continues to be a tried-and-true method of managing critical data aspects from both the business and technical perspective. Like any tool or methodology, there is a “right tool for the right job”, and specific model types exist for both business and technical users across operational, reporting, analytic, and other use cases. This webinar will provide an overview of the various data modeling techniques available, and how to use each for maximum value to the organization.
Tackling data quality problems requires more than a series of tactical, one off improvement projects. By their nature, many data quality problems extend across and often beyond an organization. Addressing these issues requires a holistic architectural approach combining people, process and technology. Join Donna Burbank and Nigel Turner as they provide practical ways to control data quality issues in your organization.
Data Architecture Best Practices for Today’s Rapidly Changing Data LandscapeDATAVERSITY
With the rise of the data-driven organization, the pace of innovation in data-centric technologies has been tremendous. New tools and techniques are emerging at an exponential rate, and it is difficult to keep track of the array of technological choices available to today’s data management professional.
At the same time, core fundamentals such as data quality and metadata management remain critical in order for organizations to obtain true business value from their data. This webinar will help demystify the options available: from data lake to data warehouse, to graph database, to NoSQL, and more, and how to integrate these new technologies with core architectural fundamentals that will help your organization benefit from the quick wins that are possible from these exciting technologies, while at the same time build a longer-term sustainable architecture that will support the inevitable change that will continue in the industry.
DAS Slides: Self-Service Reporting and Data Prep – Benefits & RisksDATAVERSITY
As more organizations see the value of becoming data-driven, an increasing number of business stakeholders want to become more actively involved in the reporting and preparation of critical business data. Tools and technologies have evolved to support this desire, and the ability to manage and analyze vast amounts of disparate data has become more accessible than ever before. With this increased visibility and usage of data, the need for data quality, metadata context, lineage and audit, and other core fundamental best practices is greater than ever.
How can an effective architecture & governance model be created that supports both business agility, as well as long-term sustainability and risk reduction? Where do these responsibilities lie between business and IT stakeholders? Join our panel of experts as they discuss the latest best practices, architectures, and tools that support self-service reporting and data prep to maximize benefits while at the same time reducing risk.
Data as a Profit Driver – Emerging Techniques to Monetize Data as a Strategic...DATAVERSITY
The Digital Economy is changing the way organizations do business across the globe, and is set to transform the economy on an unprecedented scale. Business optimization, and entirely new business models are emerging as data-driven technology provides unprecedented opportunity for innovation and change. In many organizations, data not only supports business profitability, but data itself has become the critical business asset.
What does it mean to leverage data as a business asset? And how can today’s data-centric technologies support the data-driven revolution? Join our expert panelists as they discuss the latest innovations in the data landscape.
The recent focus on Big Data in the data management community brings with it a paradigm shift—from the more traditional top-down, “design then build” approach to data warehousing and business intelligence, to the more bottom up, “discover and analyze” approach to analytics with Big Data. Where does data modeling fit in this new world of Big Data? Does it go away, or can it evolve to meet the emerging needs of these exciting new technologies? Join this webinar to discuss:
Big Data –A Technical & Cultural Paradigm Shift
Big Data in the Larger Information Management Landscape
Modeling & Technology Considerations
Organizational Considerations
The Role of the Data Architect in the World of Big Data
The Softer Skills Analysts need to make an impactPaul Laughlin
25 min presentation given at London Business School, to the OR Society's Analytics Network. Summarising Laughlin Consultancy's 9 step model of Softer Skills for Analysts.
Data Integrity: From speed dating to lifelong partnershipPrecisely
Governance has little to do with governance…it’s about delivering and demonstrating value. It’s one thing for your colleagues to intellectually believe in the value of data, good data, and governed data, but it’s another thing entirely to have them emotionally engaged and excited to be involved. In this presentation from the CDO Sit-Down series, Shaun Connolly, Vice President of International Strategic Services, shares his thoughts and experience on approaches to win over reluctant leaders and business teams and describe the key components of successful programs.
Business Intelligence (BI) and Data Management Basics amorshed
A one-day training course on the Concepts of Data Management and Business Intelligence (BI) in the DX age
A Basic Review of BI and DM
How to Implement BI
A review of BI Tools and 2022 Gartner Quadrant Magic
Basics of Data warehouse (DWH)
An introductions to Power BI
Components of Power BI
Steps for BI Implementation
Data Culture
Intro to ETL and ELT
OLAP files and Architecture
Digital transformation or DX review
A glance at DMBOK2.0 framework
BI Challenges
Data Governance
Data Integration
Data Security and Privacy in DMBOK2.0
Data-Driven Organization
Data and BI Maturity Model
Traditional BI
Self-service BI
who is DMP
who is BI developer
what is Metadata
what is Master data
Data Quality
Data Literacy
Benefits of BI
BI features
How does BI Works?
Modern BI
Data Analytics
BI Architecture
Data Types
Data Lake
Data Mart
Data Silo
Data Visualization
Power BI Architecture and components
Metadata is hotter than ever, according a number of recent DATAVERSITY surveys. More and more organizations are realizing that in order to drive business value from data, robust metadata is needed to gain the necessary context and lineage around key data assets. At the same time, industry regulations are driving the need for better transparency and understanding of information.
While metadata has been managed for decades, new strategies & approaches have been developed to support the ever-evolving data landscape, and provide more innovative ways to drive business value from metadata. This webinar will provide an overview of metadata strategies & technologies available to today’s organization, and provide insights into building successful business strategies for metadata adoption & use.
Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how data architecture is a key component of an overall enterprise architecture for enhanced business value and success.
Similar to LDM Slides: Conceptual Data Models - How to Get the Attention of Business Users (for a Technical Audience) (20)
Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...DATAVERSITY
Organizations today need a broad set of enterprise data cloud services with key data functionality to modernize applications and utilize machine learning. They need a comprehensive platform designed to address multi-faceted needs by offering multi-function data management and analytics to solve the enterprise’s most pressing data and analytic challenges in a streamlined fashion.
In this research-based session, I’ll discuss what the components are in multiple modern enterprise analytics stacks (i.e., dedicated compute, storage, data integration, streaming, etc.) and focus on total cost of ownership.
A complete machine learning infrastructure cost for the first modern use case at a midsize to large enterprise will be anywhere from $3 million to $22 million. Get this data point as you take the next steps on your journey into the highest spend and return item for most companies in the next several years.
Data at the Speed of Business with Data Mastering and GovernanceDATAVERSITY
Do you ever wonder how data-driven organizations fuel analytics, improve customer experience, and accelerate business productivity? They are successful by governing and mastering data effectively so they can get trusted data to those who need it faster. Efficient data discovery, mastering and democratization is critical for swiftly linking accurate data with business consumers. When business teams can quickly and easily locate, interpret, trust, and apply data assets to support sound business judgment, it takes less time to see value.
Join data mastering and data governance experts from Informatica—plus a real-world organization empowering trusted data for analytics—for a lively panel discussion. You’ll hear more about how a single cloud-native approach can help global businesses in any economy create more value—faster, more reliably, and with more confidence—by making data management and governance easier to implement.
What is data literacy? Which organizations, and which workers in those organizations, need to be data-literate? There are seemingly hundreds of definitions of data literacy, along with almost as many opinions about how to achieve it.
In a broader perspective, companies must consider whether data literacy is an isolated goal or one component of a broader learning strategy to address skill deficits. How does data literacy compare to other types of skills or “literacy” such as business acumen?
This session will position data literacy in the context of other worker skills as a framework for understanding how and where it fits and how to advocate for its importance.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace – from digital transformation, to marketing, to customer centricity, to population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Uncover how your business can save money and find new revenue streams.
Driving profitability is a top priority for companies globally, especially in uncertain economic times. It's imperative that companies reimagine growth strategies and improve process efficiencies to help cut costs and drive revenue – but how?
By leveraging data-driven strategies layered with artificial intelligence, companies can achieve untapped potential and help their businesses save money and drive profitability.
In this webinar, you'll learn:
- How your company can leverage data and AI to reduce spending and costs
- Ways you can monetize data and AI and uncover new growth strategies
- How different companies have implemented these strategies to achieve cost optimization benefits
Data Catalogs Are the Answer – What is the Question?DATAVERSITY
Organizations with governed metadata made available through their data catalog can answer questions their people have about the organization’s data. These organizations get more value from their data, protect their data better, gain improved ROI from data-centric projects and programs, and have more confidence in their most strategic data.
Join Bob Seiner for this lively webinar where he will talk about the value of a data catalog and how to build the use of the catalog into your stewards’ daily routines. Bob will share how the tool must be positioned for success and viewed as a must-have resource that is a steppingstone and catalyst to governed data across the organization.
Data Catalogs Are the Answer – What Is the Question?DATAVERSITY
Organizations with governed metadata made available through their data catalog can answer questions their people have about the organization’s data. These organizations get more value from their data, protect their data better, gain improved ROI from data-centric projects and programs, and have more confidence in their most strategic data.
Join Bob Seiner for this lively webinar where he will talk about the value of a data catalog and how to build the use of the catalog into your stewards’ daily routines. Bob will share how the tool must be positioned for success and viewed as a must-have resource that is a steppingstone and catalyst to governed data across the organization.
In this webinar, Bob will focus on:
-Selecting the appropriate metadata to govern
-The business and technical value of a data catalog
-Building the catalog into people’s routines
-Positioning the data catalog for success
-Questions the data catalog can answer
Because every organization produces and propagates data as part of their day-to-day operations, data trends are becoming more and more important in the mainstream business world’s consciousness. For many organizations in various industries, though, comprehension of this development begins and ends with buzzwords: “Big Data,” “NoSQL,” “Data Scientist,” and so on. Few realize that all solutions to their business problems, regardless of platform or relevant technology, rely to a critical extent on the data model supporting them. As such, data modeling is not an optional task for an organization’s data effort, but rather a vital activity that facilitates the solutions driving your business. Since quality engineering/architecture work products do not happen accidentally, the more your organization depends on automation, the more important the data models driving the engineering and architecture activities of your organization. This webinar illustrates data modeling as a key activity upon which so much technology and business investment depends.
Specific learning objectives include:
- Understanding what types of challenges require data modeling to be part of the solution
- How automation requires standardization on derivable via data modeling techniques
- Why only a working partnership between data and the business can produce useful outcomes
Analytics play a critical role in supporting strategic business initiatives. Despite the obvious value to analytic professionals of providing the analytics for these initiatives, many executives question the economic return of analytics as well as data lakes, machine learning, master data management, and the like.
Technology professionals need to calculate and present business value in terms business executives can understand. Unfortunately, most IT professionals lack the knowledge required to develop comprehensive cost-benefit analyses and return on investment (ROI) measurements.
This session provides a framework to help technology professionals research, measure, and present the economic value of a proposed or existing analytics initiative, no matter the form that the business benefit arises. The session will provide practical advice about how to calculate ROI and the formulas, and how to collect the necessary information.
How a Semantic Layer Makes Data Mesh Work at ScaleDATAVERSITY
Data Mesh is a trending approach to building a decentralized data architecture by leveraging a domain-oriented, self-service design. However, the pure definition of Data Mesh lacks a center of excellence or central data team and doesn’t address the need for a common approach for sharing data products across teams. The semantic layer is emerging as a key component to supporting a Hub and Spoke style of organizing data teams by introducing data model sharing, collaboration, and distributed ownership controls.
This session will explain how data teams can define common models and definitions with a semantic layer to decentralize analytics product creation using a Hub and Spoke architecture.
Attend this session to learn about:
- The role of a Data Mesh in the modern cloud architecture.
- How a semantic layer can serve as the binding agent to support decentralization.
- How to drive self service with consistency and control.
Enterprise data literacy. A worthy objective? Certainly! A realistic goal? That remains to be seen. As companies consider investing in data literacy education, questions arise about its value and purpose. While the destination – having a data-fluent workforce – is attractive, we wonder how (and if) we can get there.
Kicking off this webinar series, we begin with a panel discussion to explore the landscape of literacy, including expert positions and results from focus groups:
- why it matters,
- what it means,
- what gets in the way,
- who needs it (and how much they need),
- what companies believe it will accomplish.
In this engaging discussion about literacy, we will set the stage for future webinars to answer specific questions and feature successful literacy efforts.
The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...DATAVERSITY
Change is hard, especially in response to negative stimuli or what is perceived as negative stimuli. So organizations need to reframe how they think about data privacy, security and governance, treating them as value centers to 1) ensure enterprise data can flow where it needs to, 2) prevent – not just react – to internal and external threats, and 3) comply with data privacy and security regulations.
Working together, these roles can accelerate faster access to approved, relevant and higher quality data – and that means more successful use cases, faster speed to insights, and better business outcomes. However, both new information and tools are required to make the shift from defense to offense, reducing data drama while increasing its value.
Join us for this panel discussion with experts in these fields as they discuss:
- Recent research about where data privacy, security and governance stand
- The most valuable enterprise data use cases
- The common obstacles to data value creation
- New approaches to data privacy, security and governance
- Their advice on how to shift from a reactive to resilient mindset/culture/organization
You’ll be educated, entertained and inspired by this panel and their expertise in using the data trifecta to innovate more often, operate more efficiently, and differentiate more strategically.
Emerging Trends in Data Architecture – What’s the Next Big Thing?DATAVERSITY
With technological innovation and change occurring at an ever-increasing rate, it’s hard to keep track of what’s hype and what can provide practical value for your organization. Join this webinar to see the results of a recent DATAVERSITY survey on emerging trends in Data Architecture, along with practical commentary and advice from industry expert Donna Burbank.
Data Governance Trends - A Look Backwards and ForwardsDATAVERSITY
As DATAVERSITY’s RWDG series hurdles into our 12th year, this webinar takes a quick look behind us, evaluates the present, and predicts the future of Data Governance. Based on webinar numbers, hot Data Governance topics have evolved over the years from policies and best practices, roles and tools, data catalogs and frameworks, to supporting data mesh and fabric, artificial intelligence, virtualization, literacy, and metadata governance.
Join Bob Seiner as he reflects on the past and what has and has not worked, while sharing examples of enterprise successes and struggles. In this webinar, Bob will challenge the audience to stay a step ahead by learning from the past and blazing a new trail into the future of Data Governance.
In this webinar, Bob will focus on:
- Data Governance’s past, present, and future
- How trials and tribulations evolve to success
- Leveraging lessons learned to improve productivity
- The great Data Governance tool explosion
- The future of Data Governance
Data Governance Trends and Best Practices To Implement TodayDATAVERSITY
Would you share your bank account information on social media? How about shouting your social security number on the New York City subway? We didn’t think so either – that’s why data governance is consistently top of mind.
In this webinar, we’ll discuss the common Cloud data governance best practices – and how to apply them today. Join us to uncover Google Cloud’s investment in data governance and learn practical and doable methods around key management and confidential computing. Hear real customer experiences and leave with insights that you can share with your team. Let’s get solving.
Topics that you will hear addressed in this webinar:
- Understanding the basics of Cloud Incident Response (IR) and anticipated data governance trends
- Best practices for key management and apply data governance to your day-to-day
- The next wave of Confidential Computing and how to get started, including a demo
It is a fascinating, explosive time for enterprise analytics.
It is from the position of analytics leadership that the enterprise mission will be executed and company leadership will emerge. The data professional is absolutely sitting on the performance of the company in this information economy and has an obligation to demonstrate the possibilities and originate the architecture, data, and projects that will deliver analytics. After all, no matter what business you’re in, you’re in the business of analytics.
The coming years will be full of big changes in enterprise analytics and data architecture. William will kick off the fifth year of the Advanced Analytics series with a discussion of the trends winning organizations should build into their plans, expectations, vision, and awareness now.
Too often I hear the question “Can you help me with our data strategy?” Unfortunately, for most, this is the wrong request because it focuses on the least valuable component: the data strategy itself. A more useful request is: “Can you help me apply data strategically?” Yes, at early maturity phases the process of developing strategic thinking about data is more important than the actual product! Trying to write a good (must less perfect) data strategy on the first attempt is generally not productive –particularly given the widespread acceptance of Mike Tyson’s truism: “Everybody has a plan until they get punched in the face.” This program refocuses efforts on learning how to iteratively improve the way data is strategically applied. This will permit data-based strategy components to keep up with agile, evolving organizational strategies. It also contributes to three primary organizational data goals. Learn how to improve the following:
- Your organization’s data
- The way your people use data
- The way your people use data to achieve your organizational strategy
This will help in ways never imagined. Data are your sole non-depletable, non-degradable, durable strategic assets, and they are pervasively shared across every organizational area. Addressing existing challenges programmatically includes overcoming necessary but insufficient prerequisites and developing a disciplined, repeatable means of improving business objectives. This process (based on the theory of constraints) is where the strategic data work really occurs as organizations identify prioritized areas where better assets, literacy, and support (data strategy components) can help an organization better achieve specific strategic objectives. Then the process becomes lather, rinse, and repeat. Several complementary concepts are also covered, including:
- A cohesive argument for why data strategy is necessary for effective data governance
- An overview of prerequisites for effective strategic use of data strategy, as well as common pitfalls
- A repeatable process for identifying and removing data constraints
- The importance of balancing business operation and innovation
Who Should Own Data Governance – IT or Business?DATAVERSITY
The question is asked all the time: “What part of the organization should own your Data Governance program?” The typical answers are “the business” and “IT (information technology).” Another answer to that question is “Yes.” The program must be owned and reside somewhere in the organization. You may ask yourself if there is a correct answer to the question.
Join this new RWDG webinar with Bob Seiner where Bob will answer the question that is the title of this webinar. Determining ownership of Data Governance is a vital first step. Figuring out the appropriate part of the organization to manage the program is an important second step. This webinar will help you address these questions and more.
In this session Bob will share:
- What is meant by “the business” when it comes to owning Data Governance
- Why some people say that Data Governance in IT is destined to fail
- Examples of IT positioned Data Governance success
- Considerations for answering the question in your organization
- The final answer to the question of who should own Data Governance
It is clear that Data Management best practices exist and so does a useful process for improving existing Data Management practices. The question arises: Since we understand the goal, how does one design a process for Data Management goal achievement? This program describes what must be done at the programmatic level to achieve better data use and a way to implement this as part of your data program. The approach combines DMBoK content and CMMI/DMM processes – permitting organizations with the opportunity to benefit from the best of both. It also permits organizations to understand:
- Their current Data Management practices
- Strengths that should be leveraged
- Remediation opportunities
MLOps – Applying DevOps to Competitive AdvantageDATAVERSITY
MLOps is a practice for collaboration between Data Science and operations to manage the production machine learning (ML) lifecycles. As an amalgamation of “machine learning” and “operations,” MLOps applies DevOps principles to ML delivery, enabling the delivery of ML-based innovation at scale to result in:
Faster time to market of ML-based solutions
More rapid rate of experimentation, driving innovation
Assurance of quality, trustworthiness, and ethical AI
MLOps is essential for scaling ML. Without it, enterprises risk struggling with costly overhead and stalled progress. Several vendors have emerged with offerings to support MLOps: the major offerings are Microsoft Azure ML and Google Vertex AI. We looked at these offerings from the perspective of enterprise features and time-to-value.
Explore our most comprehensive guide on lookback analysis at SafePaaS, covering access governance and how it can transform modern ERP audits. Browse now!
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A personal brand exploration presentation summarizes an individual's unique qualities and goals, covering strengths, values, passions, and target audience. It helps individuals understand what makes them stand out, their desired image, and how they aim to achieve it.
The world of search engine optimization (SEO) is buzzing with discussions after Google confirmed that around 2,500 leaked internal documents related to its Search feature are indeed authentic. The revelation has sparked significant concerns within the SEO community. The leaked documents were initially reported by SEO experts Rand Fishkin and Mike King, igniting widespread analysis and discourse. For More Info:- https://news.arihantwebtech.com/search-disrupted-googles-leaked-documents-rock-the-seo-world/
Improving profitability for small businessBen Wann
In this comprehensive presentation, we will explore strategies and practical tips for enhancing profitability in small businesses. Tailored to meet the unique challenges faced by small enterprises, this session covers various aspects that directly impact the bottom line. Attendees will learn how to optimize operational efficiency, manage expenses, and increase revenue through innovative marketing and customer engagement techniques.
As a business owner in Delaware, staying on top of your tax obligations is paramount, especially with the annual deadline for Delaware Franchise Tax looming on March 1. One such obligation is the annual Delaware Franchise Tax, which serves as a crucial requirement for maintaining your company’s legal standing within the state. While the prospect of handling tax matters may seem daunting, rest assured that the process can be straightforward with the right guidance. In this comprehensive guide, we’ll walk you through the steps of filing your Delaware Franchise Tax and provide insights to help you navigate the process effectively.
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Unveiling the Secrets How Does Generative AI Work.pdfSam H
At its core, generative artificial intelligence relies on the concept of generative models, which serve as engines that churn out entirely new data resembling their training data. It is like a sculptor who has studied so many forms found in nature and then uses this knowledge to create sculptures from his imagination that have never been seen before anywhere else. If taken to cyberspace, gans work almost the same way.
Remote sensing and monitoring are changing the mining industry for the better. These are providing innovative solutions to long-standing challenges. Those related to exploration, extraction, and overall environmental management by mining technology companies Odisha. These technologies make use of satellite imaging, aerial photography and sensors to collect data that might be inaccessible or from hazardous locations. With the use of this technology, mining operations are becoming increasingly efficient. Let us gain more insight into the key aspects associated with remote sensing and monitoring when it comes to mining.
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What are the main advantages of using HR recruiter services.pdfHumanResourceDimensi1
HR recruiter services offer top talents to companies according to their specific needs. They handle all recruitment tasks from job posting to onboarding and help companies concentrate on their business growth. With their expertise and years of experience, they streamline the hiring process and save time and resources for the company.
India Orthopedic Devices Market: Unlocking Growth Secrets, Trends and Develop...Kumar Satyam
According to TechSci Research report, “India Orthopedic Devices Market -Industry Size, Share, Trends, Competition Forecast & Opportunities, 2030”, the India Orthopedic Devices Market stood at USD 1,280.54 Million in 2024 and is anticipated to grow with a CAGR of 7.84% in the forecast period, 2026-2030F. The India Orthopedic Devices Market is being driven by several factors. The most prominent ones include an increase in the elderly population, who are more prone to orthopedic conditions such as osteoporosis and arthritis. Moreover, the rise in sports injuries and road accidents are also contributing to the demand for orthopedic devices. Advances in technology and the introduction of innovative implants and prosthetics have further propelled the market growth. Additionally, government initiatives aimed at improving healthcare infrastructure and the increasing prevalence of lifestyle diseases have led to an upward trend in orthopedic surgeries, thereby fueling the market demand for these devices.
RMD24 | Debunking the non-endemic revenue myth Marvin Vacquier Droop | First ...BBPMedia1
Marvin neemt je in deze presentatie mee in de voordelen van non-endemic advertising op retail media netwerken. Hij brengt ook de uitdagingen in beeld die de markt op dit moment heeft op het gebied van retail media voor niet-leveranciers.
Retail media wordt gezien als het nieuwe advertising-medium en ook mediabureaus richten massaal retail media-afdelingen op. Merken die niet in de betreffende winkel liggen staan ook nog niet in de rij om op de retail media netwerken te adverteren. Marvin belicht de uitdagingen die er zijn om echt aansluiting te vinden op die markt van non-endemic advertising.
RMD24 | Debunking the non-endemic revenue myth Marvin Vacquier Droop | First ...
LDM Slides: Conceptual Data Models - How to Get the Attention of Business Users (for a Technical Audience)
1. Conceptual Data Models -
How to Get the Attention of Business Users
Donna Burbank
Global Data Strategy Ltd.
Lessons in Data Modeling DATAVERSITY Series
March 23rd, 2017
2. Global Data Strategy, Ltd. 2017
Donna Burbank
Donna is a recognised industry expert in
information management with over 20
years of experience in data strategy,
information management, data modeling,
metadata management, and enterprise
architecture. Her background is multi-
faceted across consulting, product
development, product management,
brand strategy, marketing, and business
leadership.
She is currently the Managing Director at
Global Data Strategy, Ltd., an international
information management consulting
company that specialises in the alignment
of business drivers with data-centric
technology. In past roles, she has served in
key brand strategy and product
management roles at CA Technologies and
Embarcadero Technologies for several of
the leading data management products in
the market.
As an active contributor to the data
management community, she is a long
time DAMA International member and is
the Past President & Advisor to the DAMA
Rocky Mountain chapter. She was also on
the review committee for the Object
Management Group’s Information
Management Metamodel (IMM) and a
member of the OMG’s Finalization
Taskforce for the Business Process
Modeling Notation (BPMN).
She has worked with dozens of Fortune
500 companies worldwide in the
Americas, Europe, Asia, and Africa and
speaks regularly at industry
conferences. She has co-authored two
books: Data Modeling for the
Business and Data Modeling Made Simple
with ERwin Data Modeler and is a regular
contributor to industry publications.
She can be reached at
donna.burbank@globaldatastrategy.com
Donna is based in Boulder, Colorado, USA.
2
Follow on Twitter @donnaburbank
Today’s hashtag: #LessonsDM
3. Global Data Strategy, Ltd. 2017
Lessons in Data Modeling Series
• January 26th How Data Modeling Fits Into an Overall Enterprise Architecture
• February 23rd Data Modeling and Business Intelligence
• March Conceptual Data Modeling – How to Get the Attention of Business Users
• April The Evolving Role of the Data Architect – What does it mean for your Career?
• May Data Modeling & Metadata Management
• June Self-Service Data Analysis, Data Wrangling, Data Munging, and Data Modeling
• July Data Modeling & Metadata for Graph Databases
• August Data Modeling & Data Integration
• September Data Modeling & MDM
• October Agile & Data Modeling – How Can They Work Together?
• December Data Modeling, Data Quality & Data Governance
3
This Year’s Line Up
4. Global Data Strategy, Ltd. 2017
A Data Model Facilitates Communication
• A Conceptual Data Model Facilitates Communication between Business and IT
• Focus on (business) audience
• Intuitive display
• Capture the business rules and definitions in your model
• Simplicity does not mean lack of importance
• A simple model can express important concepts
• Ignoring the key business definitions can have negative affects
• A model or tool is only part of the solution
• Communication is key
• Process and Best Practices are critical to achieve consensus and buy-in
5. Global Data Strategy, Ltd. 2017
Data Models are a Key Part of any Data or Business Strategy
5
A Successful Data Strategy links Business Goals with Technology Solutions
“Top-Down” alignment with
business priorities
“Bottom-Up” management &
inventory of data sources
Managing the people, process,
policies & culture around data
Coordinating & integrating
disparate data sources
Leveraging & managing data for
strategic advantage
6. Global Data Strategy, Ltd. 2017
Focusing on the Business View
6
Conceptual
Logical
Physical
Purpose
Communication & Definition of
Business Terms & Rules
Clarification & Detail
of Business Rules &
Data Structures
Technical
Implementation on
a Physical Database
Audience
Business Stakeholders
Data Architecture
Business Analysts
DBAs
Developers
Business Concepts
Data Entities
Physical Tables
• When data modeling from a business perspective, focus on the Conceptual & Logical models.
7. Global Data Strategy, Ltd. 2017
What is in a Name?
• In an industry that’s focused on creating common terms definitions…
• …We’re terrible at creating common terms & definitions.
7
Or…the Cobblers Children Have No Shoes
• In a survey of data professionals, the most popular names for
the Conceptual (high-level) model included1:
• Conceptual Data Model 59%
• Subject Area Model 12%
• Business Data Model 10%
• Enterprise Data Model 6%
• Other names 13%
1
8. Global Data Strategy, Ltd. 2017
Technical & Business Metadata
• Technical Metadata describes the structure, format, and rules for storing data
• Business Metadata describes the business definitions, rules, and context for data.
• Data represents actual instances (e.g. John Smith)
8
CREATE TABLE EMPLOYEE (
employee_id INTEGER NOT NULL,
department_id INTEGER NOT NULL,
employee_fname VARCHAR(50) NULL,
employee_lname VARCHAR(50) NULL,
employee_ssn CHAR(9) NULL);
CREATE TABLE CUSTOMER (
customer_id INTEGER NOT NULL,
customer_name VARCHAR(50) NULL,
customer_address VARCHAR(150) NULL,
customer_city VARCHAR(50) NULL,
customer_state CHAR(2) NULL,
customer_zip CHAR(9) NULL);
Technical Metadata
John Smith
Business Metadata
Data
Term Definition
Employee
An employee is an individual who currently
works for the organization or who has been
recently employed within the past 6 months.
Customer
A customer is a person or organization who
has purchased from the organization within
the past 2 years and has an active loyalty card
or maintenance contract.
9. Global Data Strategy, Ltd. 2017
Metadata is Needed by Business Stakeholders
9
Making business decisions on accurate and well-understood data
80% of users of metadata are from
the business, according to the
recent DATAVERSITY survey.
10. Global Data Strategy, Ltd. 2017
My Favorite Quote from a Business Stakeholder
10
You mean you’re NOT doing
this already??
Often the biggest challengers to conceptual data modeling & metadata come from IT, not the business.
11. Global Data Strategy, Ltd. 2017
Why Does Conceptual Modeling Matter?
• You’ve been tasked to assist in the creation of a Business Intelligence (BI) reporting application for Customers.
• Technical and political challenges exist
Numerous systems have been built already—different platforms and databases
Parties cannot agree on a single definition of what a ‘customer’ is
• Our Proposed Solution: Start with a Conceptual Data Model
• What is the definition of customer?
• Where is the data stored?
• How is it structured?
• Who uses or owns the data?
Data Warehouse BI Report:
Customers by Region
• What are the definitions of key business terms?
• What do I want to report on?
• How do I optimize the database for these reports?
Data Modeling helps answer:
For Data Warehousing For BI Reporting
Data Modeling helps answer:Show me all
customers by region
Source Systems
Relational Model
Dimensional Model
An Example
12. Global Data Strategy, Ltd. 2017
Building a Conceptual Data Model
• We start with a very simple data model, with just one object on it, called “Customer”.
• We use an ER Model and show business definitions
Starting with the basics
Too Simple??
13. Global Data Strategy, Ltd. 2017
Too Simple?
• Our team thought so, so went ahead and focused on the technical integration, including:
• Reverse engineering a physical model from each system
• Creating ETL scripts
• Migrating the data into a data warehouse
• Building a reporting system off of the data
• The results?
• This implementation went “perfectly”, with no errors in the scripts, no data type
inconsistencies, no delays in schedule, etc.
• We built a complex BI reporting system to show our upper management the results.
• We even sent out a welcome email to all of our customers, giving them a 50% off coupon,
and thanking them for their support.
14. Global Data Strategy, Ltd. 2017
Focusing on the Business
• Until we showed the report to the business sponsor:
• We can’t have 2000 customers in this region! I know we only have around 400!
• Why is Jones’ Tire on this list? They are still evaluating our product! Sales was negotiating a
10% discount with them, and you just sent them a 50% coupon!?!?
• You just spent all of that money in IT to build this report with bad data???
15. Global Data Strategy, Ltd. 2017
Oops!
• We were mixing current customers, with prospects (non-customers).
• We just sent a discount coupon to 1600 of the wrong people!
• We gave upper management a report showing the wrong figure for our total number of
customers!
• We are now significantly over budget to have to go back and fix this!!
• We started over, this time with a Conceptual Data Model
16. Global Data Strategy, Ltd. 2017
The Importance of Business Definitions
From Data Modeling for the Business by
Hoberman, Burbank, Bradley, Technics
Publications, 2009
17. Global Data Strategy, Ltd. 2017
Use the Language of Your Audience
• When communicating with business stakeholders, it’s important to display data models in a way
that’s intuitive to them
• PowerPoint-style Conceptual Data Models
• Use Business Terminology
• Avoid Excess Detail
17
Gaining Buy-In
19. Global Data Strategy, Ltd. 2017
The Eternal Question…
19
Can and Should a Businessperson
learn Data Modeling notation?
20. Global Data Strategy, Ltd. 2017
When?
What is an Entity?
The “Who, What, Where, When, Why” of the Organization – the Nouns
Entity: A classification of the types of objects found in the
real world --persons, places, things, concepts and events – of
interest to the enterprise. 1
1 DAMA Dictionary of Data ManagementWho?
How?
Where?
What?
Product
Salesperson
Invoice
Why?
Order
Period
Location
21. Global Data Strategy, Ltd. 2017
Attributes
• An Attribute is a piece of information about or a characteristic of an Entity.
Attributes provide more detail about an Entity
Attributes
Entity
Employee • Employee Identifier
• Employee Last Name
• Employee First Name
• Employee Hire Date
• Employee Signed Employment Contract
• Employee Drivers License Photo
Entity
Attributes
22. Global Data Strategy, Ltd. 2017
— Relationships are the “lines” on a data model
Relationships are the “Verbs” of the Organization
• Relationships define the data-centric Business Rules of an organization
• An employee can work for more than one department.
• A customer can have more than one account.
• Sales are reported monthly.
• A department can contain more than one employee.
Defining Business Rules
— Relationships are the “verbs” in a sentence.
—A department can contain more than one employee.
23. Global Data Strategy, Ltd. 2017
Deciphering Cardinality
Think of how a child might answer the question “How many?”
One = 1 finger
More than one = several fingers
24. Global Data Strategy, Ltd. 2017
Supertypes & Subtypes
• Some Entities naturally split into Sub-Types in a Organization:
• Exclusive: i.e. “Either/Or” - a member of the supertype can only one subtype role. For example, a
Vehicle can be a Car or a Truck, but not both.
• Inclusive: i.e. “And” - a member of the supertype can play more than one subtype role. For example, a
Person can be both a Customer and Employee.
24
Vehicle
Customer
Person
EmployeeCar Truck
Exclusive Inclusive
25. Global Data Strategy, Ltd. 2017
Use the Language of Your Audience
Use Business Terms, not Theoretical Ones
25
Use Business Terminology
May be academically correct, but too
vague to be useful for business users.This?
Or
This?
Or
This?
26. Global Data Strategy, Ltd. 2017
Keep the Focus on the Business
• Debate actual differences in business meaning, not academic theory
• Determine why differences occur:
• Is this a different entity?
• Different names for the same entity?
• A Supertype / Subtype relationship?
• Etc.
26
Fight the Right Battles
VS. VS. VS.
27. Global Data Strategy, Ltd. 2017
The Importance of Definitions
• Definitions are as important as the data elements themselves.
• Many data-related business issues are caused by unclear or ill-defined terms
27
What do you mean by
“customer”?
We’re calculating “total sales”
differently in each region!
Sales is using a different
“monthly calendar” than
Finance.
How are we defining a
“household”?
What’s an “equity
derivative”?
What’s a “PEG ratio”?
“API” as in “Application Programming Interface?”
or “American Petroleum Institute”? Or a bee?
What’s the difference between an
“ingredient” and a “raw material”?
28. Global Data Strategy, Ltd. 2017
Store & Display Definitions in a Data Model
28
• Data Models are a great place to store business definitions
• Display them on the model for a business audience
• Store them in the model repository for reuse across the organization (various users, tools, etc.)
29. Global Data Strategy, Ltd. 2017
Human Metadata
• Much business metadata and the history of the business exists in employee’s heads.
• It is important to capture this metadata in an electronic format for sharing with others.
• Avoid the dreaded “I just know”
29
Avoid the dreaded “I just know”
Part Number is what used to
be called Component
Number before the
acquisition.
Business Glossary
Metadata Repository
Data Models
Etc.
30. Global Data Strategy, Ltd. 2017
Better Definitions Drive Better Communication
• Wouldn’t it be helpful if we did this in daily life, too?
• i.e. “Let’s go on a family vacation!”
Person Concept Definition
Father Vacation An opportunity to take the time to achieve new goals
Mother Vacation Time to relax and read a book
Jane Vacation A chance to get outside and exercise
Bobby Vacation Time to be with friends
Donna Vacation More time to build data models
Ian Holiday You Americans use crazy words for things
31. Global Data Strategy, Ltd. 2017
A Data Model Is a Visual Representation of Core Concepts
31From Data Modeling for the Business by Hoberman, Burbank, Bradley, Technics Publications, 2009
A data model is a graphical view of the core concepts important to the organization.
Humans tend to think in Pictures.
32. Global Data Strategy, Ltd. 2017 32
Customer
Prospect
Salesperson
Is Father Of
Is Evaluating
Sells
Household
Product
Buys
Buys
Customer
Support Rep
Supports
Sells To
Is Trained On
Client
A Data Model Describes a Business
• When working with a business audience, the importance of a data model is in communication.
• Use creative ways to show models to a business audience.
• The data model should tell the “story” of the business.
Be Creative in your Data Model Presentation
33. Global Data Strategy, Ltd. 2017
Tell a Story
• Humans have evolved over time as storytellers
• We can’t even sleep without dreaming in stories.
• No one cares about your data model…
• … but they do care about the RESULTS of your data model
• … relate the model to a real world impact or scenario..i.e.
“story”
33
What impact does the data model have on the business?
Humans are Storytellers.
From Data Modeling for the Business by Hoberman, Burbank, Bradley, Technics Publications, 2009
34. Global Data Strategy, Ltd. 2017
Business Executive
• Results-Oriented
• Optimistic – Identifies opportunities
• “I’m busy.”
• “What’s the business opportunity?”
Data Architect
• Focused on architecture, data, technology
• Often seen as finding problems, not
solutions
• “Let me tell you about my data model!”
Data Advisor
• Focused on solutions, business, information
• Highlights issues & opportunities around
data
• “Less me show you how data can help your
business!”
The world is going to end if your
model is not in 3rd normal form!!
If you link your Customer data with
your Product usage stats, we can
increase sales.
What’s in it for me?
Be More “Data Advisor” and Less “Data Architect”
35. Global Data Strategy, Ltd. 2017
We Do It, Too – We Care about Results, not Details!
35
Do we really care about the details of other people’s jobs?
We recently switched to accrual-
based accounting from cash-based
accounting to optimize…
I just want my
paycheck.
Accountant Data Architect
36. Global Data Strategy, Ltd. 2017
The “Elevator Pitch”
36
How Would you Describe Your Project to the CEO in 2 minutes?
VS.
I’m working on a project to
rationalize metadata across data
sources to ensure consistency…
Zzzzzzzz…
I’m working on a project to get a
more complete view of
customers for the big online
marketing campaign…
Interesting!
37. Global Data Strategy, Ltd. 2017
Summary
• With Conceptual Models, the focus is on the business
• Communication with business stakeholders
• Identification of business definitions & rules
• Tailor your presentation & language to suit your audience
• Graphics and visual presentation are easy to understand
• Use Business terminology, not theoretical or technical terms
• Business people can understand data models if used correctly
• Work on your “Elevator Pitch”
• Tell a “story” that relates to an actual business opportunity or problem
• Focus on results
• Eschew Obfuscation!
38. Global Data Strategy, Ltd. 2017
Contact Info
• Email: donna.burbank@globaldatastrategy.com
• Twitter: @donnaburbank
@GlobalDataStrat
• Website: www.globaldatastrategy.com
• Company Linkedin: https://www.linkedin.com/company/global-data-strategy-ltd
• Personal Linkedin: https://www.linkedin.com/in/donnaburbank
38
39. Global Data Strategy, Ltd. 2017
About Global Data Strategy, Ltd
• Global Data Strategy is an international information management consulting company that specializes
in the alignment of business drivers with data-centric technology.
• Our passion is data, and helping organizations enrich their business opportunities through data and
information.
• Our core values center around providing solutions that are:
• Business-Driven: We put the needs of your business first, before we look at any technology solution.
• Clear & Relevant: We provide clear explanations using real-world examples.
• Customized & Right-Sized: Our implementations are based on the unique needs of your organization’s
size, corporate culture, and geography.
• High Quality & Technically Precise: We pride ourselves in excellence of execution, with years of
technical expertise in the industry.
39
Data-Driven Business Transformation
Business Strategy
Aligned With
Data Strategy
Visit www.globaldatastrategy.com for more information
40. Global Data Strategy, Ltd. 2017
DATAVERSITY Training Center
• Learn the basics of Metadata Management and practical tips on how to apply metadata
management in the real world. This online course hosted by DATAVERSITY provides a series of six
courses including:
• What is Metadata
• The Business Value of Metadata
• Sources of Metadata
• Metamodels and Metadata Standards
• Metadata Architecture, Integration, and Storage
• Metadata Strategy and Implementation
• Purchase all six courses for $399 or individually at $79 each.
Register here
• Other courses available on Data Governance & Data Quality
40
Online Training Courses
Metadata Management Course
Visit: http://training.dataversity.net/lms/
41. Global Data Strategy, Ltd. 2017
Lessons in Data Modeling Series
• January 26th How Data Modeling Fits Into an Overall Enterprise Architecture
• February 23rd Data Modeling and Business Intelligence
• March Conceptual Data Modeling – How to Get the Attention of Business Users
• April The Evolving Role of the Data Architect – What does it mean for your Career?
• May Data Modeling & Metadata Management
• June Self-Service Data Analysis, Data Wrangling, Data Munging, and Data Modeling
• July Data Modeling & Metadata for Graph Databases
• August Data Modeling & Data Integration
• September Data Modeling & MDM
• October Agile & Data Modeling – How Can They Work Together?
• December Data Modeling, Data Quality & Data Governance
41
This Year’s Line Up