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
Do-It-Yourself (DIY) Data Governance FrameworkDATAVERSITY
A worthwhile Data Governance framework includes the core component of a successful program as viewed by the different levels of the organization. Each of the components is addressed at each of the levels, providing insight into key ideas and terminology used to attract participation across the organization. A framework plays a key role in setting up and sustaining a Data Governance program.
In this RWDG webinar, Bob Seiner will share two frameworks. The first is a basic cross-reference of components and levels, while the second can be used to compare and contrast different approaches to implementing Data Governance. When this webinar is finished, you will be able to customize the frameworks to outline the most appropriate manner for you to improve your likelihood of DG success.
In this webinar, Bob will discuss and share:
- Customizing a framework to match organizational requirements
- The core components and levels of an industry framework
- How to complete a Data Governance framework
- Using the framework to enable DG program success
- Measuring value through the DIY DG framework
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
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
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!
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 Nigel Turner and Donna Burbank as they provide practical ways to control Data Quality issues in your organization.
How to Implement Data Governance Best PracticeDATAVERSITY
Data Governance Best Practice is defined as basis and guidelines for suggested governing activities. Organizations define best practices to be used as a point of comparison when determining their readiness, willingness and actions necessary to put a Data Governance program in place. But what are the best practices and how can they be implemented? This webinar will address these questions and more.
In this RWDG webinar, Bob Seiner will talk about how to create, validate, assess and implement Data Governance Best Practice with immediate impact on present and future Data Governance activities. The result of a Best Practice assessment is a thorough actionable plan focused on demonstrating value from your Data Governance program.This webinar will cover:
• Two Criteria for Data Governance Best Practice Development
• How to Assess against Best Practice to Build Program Success
• Examples of Industry Selected DG Best Practice
• How to Communicate DG Best Practice in a Non-Threatening Way
• How to Build DG Best Practice into Daily Operations
Do-It-Yourself (DIY) Data Governance FrameworkDATAVERSITY
A worthwhile Data Governance framework includes the core component of a successful program as viewed by the different levels of the organization. Each of the components is addressed at each of the levels, providing insight into key ideas and terminology used to attract participation across the organization. A framework plays a key role in setting up and sustaining a Data Governance program.
In this RWDG webinar, Bob Seiner will share two frameworks. The first is a basic cross-reference of components and levels, while the second can be used to compare and contrast different approaches to implementing Data Governance. When this webinar is finished, you will be able to customize the frameworks to outline the most appropriate manner for you to improve your likelihood of DG success.
In this webinar, Bob will discuss and share:
- Customizing a framework to match organizational requirements
- The core components and levels of an industry framework
- How to complete a Data Governance framework
- Using the framework to enable DG program success
- Measuring value through the DIY DG framework
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
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
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!
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 Nigel Turner and Donna Burbank as they provide practical ways to control Data Quality issues in your organization.
How to Implement Data Governance Best PracticeDATAVERSITY
Data Governance Best Practice is defined as basis and guidelines for suggested governing activities. Organizations define best practices to be used as a point of comparison when determining their readiness, willingness and actions necessary to put a Data Governance program in place. But what are the best practices and how can they be implemented? This webinar will address these questions and more.
In this RWDG webinar, Bob Seiner will talk about how to create, validate, assess and implement Data Governance Best Practice with immediate impact on present and future Data Governance activities. The result of a Best Practice assessment is a thorough actionable plan focused on demonstrating value from your Data Governance program.This webinar will cover:
• Two Criteria for Data Governance Best Practice Development
• How to Assess against Best Practice to Build Program Success
• Examples of Industry Selected DG Best Practice
• How to Communicate DG Best Practice in a Non-Threatening Way
• How to Build DG Best Practice into Daily Operations
Creating a clearly articulated data strategy—a roadmap of technology-driven capability investments prioritized to deliver value—helps ensure from the get-go that you are focusing on the right things, so that your work with data has a business impact. In this presentation, the experts at Silicon Valley Data Science share their approach for crafting an actionable and flexible data strategy to maximize business value.
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.
Customer-Centric Data Management for Better Customer ExperiencesInformatica
With consumer and business buyer expectations growing exponentially, more businesses are competing on the basis of customer experience. But executing preferred customer experiences requires data about who your customers are today and what will they likely need in the future. Every business can benefit from an AI-powered master data management platform to supply this information to line-of-business owners so they can execute great experiences at scale. This same need is true from an internal business process perspective as well. For example, many businesses require better data management practices to deliver preferred employee experiences. Informatica provides an MDM platform to solve for these examples and more.
You Need a Data Catalog. Do You Know Why?Precisely
The data catalog has become a popular discussion topic within data management and data governance circles. A data catalog is a central repository that contains metadata for describing data sets, how they are defined, and where to find them. TDWI research indicates that implementing a data catalog is a top priority among organizations we survey. The data catalog can also play an important part in the governance process. It provides features that help ensure data quality, compliance, and that trusted data is used for analysis. Without an in-depth knowledge of data and associated metadata, organizations cannot truly safeguard and govern their data.
Join this on-demand webinar to learn more about the data catalog and its role in data governance efforts.
Topics include:
· Data management challenges and priorities
· The modern data catalog – what it is and why it is important
· The role of the modern data catalog in your data quality and governance programs
· The kinds of information that should be in your data catalog and why
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.
Data Architecture Strategies: Data Architecture for Digital TransformationDATAVERSITY
MDM, data quality, data architecture, and more. At the same time, combining these foundational data management approaches with other innovative techniques can help drive organizational change as well as technological transformation. This webinar will provide practical steps for creating a data foundation for effective digital transformation.
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.
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
In business, master data management is a method used to define and manage the critical data of an organization to provide, with data integration, a single point of reference.
How to Strengthen Enterprise Data Governance with Data QualityDATAVERSITY
If your organization is in a highly-regulated industry – or relies on data for competitive advantage – data governance is undoubtedly a top priority. Whether you’re focused on “defensive” data governance (supporting regulatory compliance and risk management) or “offensive” data governance (extracting the maximum value from your data assets, and minimizing the cost of bad data), data quality plays a critical role in ensuring success.
Join our webinar to learn how enterprise data quality drives stronger data governance, including:
The overlaps between data governance and data quality
The “data” dependencies of data governance – and how data quality addresses them
Key considerations for deploying data quality for data governance
How to Make a Data Governance Program that LastsDATAVERSITY
Traditional data governance initiatives fail by focusing too heavily on policies, compliance, and enforcement, which quickly lose business interest and support. This leaves data management and governance leaders having to continually make the case for data governance to secure business adoption. Join Cameron, VP, Product Management, Precisely, as he shares a lean, business-first data governance approach that connects key initiatives to governance capabilities and quickly delivers business value for the long-term. He will give examples of organizations worldwide who have successfully implemented a data governance program by engaging with key stakeholders using innovative techniques such as gamification and data catalog scavenger hunts.
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.
Adopting a Process-Driven Approach to Master Data ManagementSoftware AG
What is a lasting solution to the sea of errors, headaches, and losses caused by inconsistent and inaccurate master data such as customer and product records? This is the data that your business counts on to operate business processes and make decisions. But this data is often incomplete or in conflict because it resides in multiple IT systems. Master Data Management (MDM)'s programs are the solution to this problem, but these programs can fail without the investment and involvement of business managers.
Listen to Rob Karel, Forrester analyst, and Jignesh Shah from Software AG to learn about a new, process-driven approach to MDM and why it is a win-win for both business and IT managers.
Visit us at http://www.softwareag.com Become part of our growing community: Facebook: http://www.facebook.com/softwareag Twitter: http://www.twitter.com/softwareag LinkedIn: http://www.linkedin.com/company/software-ag YouTube: http://www.youtube.com/softwareag
Introduction to DCAM, the Data Management Capability Assessment Model - Editi...Element22
DCAM stands for Data management Capability Assessment Model. DCAM is a model to assess data management capabilities within the financial industry. It was created by the EDM Council in collaboration with over 100 financial institutions. This presentation provides an overview of DCAM and how financial institutions leverage DCAM to improve or establish their data management programs and meet regulatory requirements such as BCBS 239. Also the benefits of DCAM are described as part of this presentation.
Becoming a Data-Driven Organization - Aligning Business & Data StrategyDATAVERSITY
More organizations are aspiring to become ‘data driven businesses’. But all too often this aim fails, as business goals and IT & data realities are misaligned, with IT lagging behind rapidly changing business needs. So how do you get the perfect fit where data strategy is driven by and underpins business strategy? This webinar will show you how by de-mystifying the building blocks of a global data strategy and highlighting a number of real world success stories. Topics include:
•How to align data strategy with business motivation and drivers
•Why business & data strategies often become misaligned & the impact
•Defining the core building blocks of a successful data strategy
•The role of business and IT
•Success stories in implementing global data strategies
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.
Creating a clearly articulated data strategy—a roadmap of technology-driven capability investments prioritized to deliver value—helps ensure from the get-go that you are focusing on the right things, so that your work with data has a business impact. In this presentation, the experts at Silicon Valley Data Science share their approach for crafting an actionable and flexible data strategy to maximize business value.
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.
Customer-Centric Data Management for Better Customer ExperiencesInformatica
With consumer and business buyer expectations growing exponentially, more businesses are competing on the basis of customer experience. But executing preferred customer experiences requires data about who your customers are today and what will they likely need in the future. Every business can benefit from an AI-powered master data management platform to supply this information to line-of-business owners so they can execute great experiences at scale. This same need is true from an internal business process perspective as well. For example, many businesses require better data management practices to deliver preferred employee experiences. Informatica provides an MDM platform to solve for these examples and more.
You Need a Data Catalog. Do You Know Why?Precisely
The data catalog has become a popular discussion topic within data management and data governance circles. A data catalog is a central repository that contains metadata for describing data sets, how they are defined, and where to find them. TDWI research indicates that implementing a data catalog is a top priority among organizations we survey. The data catalog can also play an important part in the governance process. It provides features that help ensure data quality, compliance, and that trusted data is used for analysis. Without an in-depth knowledge of data and associated metadata, organizations cannot truly safeguard and govern their data.
Join this on-demand webinar to learn more about the data catalog and its role in data governance efforts.
Topics include:
· Data management challenges and priorities
· The modern data catalog – what it is and why it is important
· The role of the modern data catalog in your data quality and governance programs
· The kinds of information that should be in your data catalog and why
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.
Data Architecture Strategies: Data Architecture for Digital TransformationDATAVERSITY
MDM, data quality, data architecture, and more. At the same time, combining these foundational data management approaches with other innovative techniques can help drive organizational change as well as technological transformation. This webinar will provide practical steps for creating a data foundation for effective digital transformation.
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.
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
In business, master data management is a method used to define and manage the critical data of an organization to provide, with data integration, a single point of reference.
How to Strengthen Enterprise Data Governance with Data QualityDATAVERSITY
If your organization is in a highly-regulated industry – or relies on data for competitive advantage – data governance is undoubtedly a top priority. Whether you’re focused on “defensive” data governance (supporting regulatory compliance and risk management) or “offensive” data governance (extracting the maximum value from your data assets, and minimizing the cost of bad data), data quality plays a critical role in ensuring success.
Join our webinar to learn how enterprise data quality drives stronger data governance, including:
The overlaps between data governance and data quality
The “data” dependencies of data governance – and how data quality addresses them
Key considerations for deploying data quality for data governance
How to Make a Data Governance Program that LastsDATAVERSITY
Traditional data governance initiatives fail by focusing too heavily on policies, compliance, and enforcement, which quickly lose business interest and support. This leaves data management and governance leaders having to continually make the case for data governance to secure business adoption. Join Cameron, VP, Product Management, Precisely, as he shares a lean, business-first data governance approach that connects key initiatives to governance capabilities and quickly delivers business value for the long-term. He will give examples of organizations worldwide who have successfully implemented a data governance program by engaging with key stakeholders using innovative techniques such as gamification and data catalog scavenger hunts.
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.
Adopting a Process-Driven Approach to Master Data ManagementSoftware AG
What is a lasting solution to the sea of errors, headaches, and losses caused by inconsistent and inaccurate master data such as customer and product records? This is the data that your business counts on to operate business processes and make decisions. But this data is often incomplete or in conflict because it resides in multiple IT systems. Master Data Management (MDM)'s programs are the solution to this problem, but these programs can fail without the investment and involvement of business managers.
Listen to Rob Karel, Forrester analyst, and Jignesh Shah from Software AG to learn about a new, process-driven approach to MDM and why it is a win-win for both business and IT managers.
Visit us at http://www.softwareag.com Become part of our growing community: Facebook: http://www.facebook.com/softwareag Twitter: http://www.twitter.com/softwareag LinkedIn: http://www.linkedin.com/company/software-ag YouTube: http://www.youtube.com/softwareag
Introduction to DCAM, the Data Management Capability Assessment Model - Editi...Element22
DCAM stands for Data management Capability Assessment Model. DCAM is a model to assess data management capabilities within the financial industry. It was created by the EDM Council in collaboration with over 100 financial institutions. This presentation provides an overview of DCAM and how financial institutions leverage DCAM to improve or establish their data management programs and meet regulatory requirements such as BCBS 239. Also the benefits of DCAM are described as part of this presentation.
Becoming a Data-Driven Organization - Aligning Business & Data StrategyDATAVERSITY
More organizations are aspiring to become ‘data driven businesses’. But all too often this aim fails, as business goals and IT & data realities are misaligned, with IT lagging behind rapidly changing business needs. So how do you get the perfect fit where data strategy is driven by and underpins business strategy? This webinar will show you how by de-mystifying the building blocks of a global data strategy and highlighting a number of real world success stories. Topics include:
•How to align data strategy with business motivation and drivers
•Why business & data strategies often become misaligned & the impact
•Defining the core building blocks of a successful data strategy
•The role of business and IT
•Success stories in implementing global data strategies
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.
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.
DAS Slides: Data Quality Best PracticesDATAVERSITY
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 Nigel Turner and Donna Burbank as they provide practical ways to control data quality issues in your organization.
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.
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, customer centricity, 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.
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.
DAS Slides: Data Quality Best PracticesDATAVERSITY
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 Nigel Turner and Donna Burbank as they provide practical ways to control Data Quality issues in your organization.
LDM Slides: Conceptual Data Models - How to Get the Attention of Business Use...DATAVERSITY
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.
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, customer centricity, 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.
Why there are so many problems with streamlining data strategy ? What are the major problems ? How do you solve them ?
Using an approach based on Agile and Lean Concepts to achieve the goal of actionable data & analytics
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.
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.
Data Governance & Data Architecture - Alignment and SynergiesDATAVERSITY
The definition of Data Governance can vary depending on the audience. To many, Data Governance consists of committees and stewardship roles. To others, it focuses on technical Data Management and controls. Holistic Data Governance combines both aspects, and a robust Data Architecture can be the “glue” that binds business and IT governance together. Join this webinar for practical tips and hands-on exercises for aligning Data Architecture and Data Governance for business and IT 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: 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: digital transformation, marketing, customer centricity, and more. This webinar will help de-mystify Data Strategy and Data Architecture and will provide concrete, practical ways to get started.
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.
DataEd Webinar: Implementing Successful Data Strategies - Developing Organiza...DATAVERSITY
Big Data projects have been about as successful as other IT projects – about 29% successful according to the 2015 Standish Group Chaos Report. Second, Data Scientists are generally assessed to be about 20% productive. The reason for both of these dismal statistics is simple—organizations are terrible about understanding how to use data as a strategic organizational resource. In fact, considering the data is our sole, non-depletable, non-degrading, durable strategic asset, it is really mind boggling how poorly it is managed. Having an actionable data strategy is the first, most critical step in exerting positive control over data and leveraging it in support of your organization's business strategy.
This talk will simply describe:
What a data strategy is and its key component pieces
How to align your data strategy with your organization’s strategic imperatives while recognizing the constraints of current state capabilities; and
How to develop actionable roadmaps that will add value to the organization’s ability to leverage and monetize its data most effectively.
Once understood, your organization will be better positioned to support its mission and take advantage of new and existing data sources while complying with relevant laws, regulations, and policies.
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.
Similar to Lessons in Data Modeling: Why a Data Model is an Important Part of Your Data Strategy (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.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Assure Contact Center Experiences for Your Customers With ThousandEyes
Lessons in Data Modeling: Why a Data Model is an Important Part of Your Data Strategy
1. Why a Data Model is an Important Part
of Your Data Strategy
Donna Burbank & Nigel Turner
Global Data Strategy Ltd.
Lessons in Data Modeling DATAVERSITY Series
July 28th, 2016
2. Global Data Strategy, Ltd. 2016
Donna Burbank
Donna is a recognized industry expert in
information management with over 20
years of experience in data
management, 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 specializes 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 President of 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 CA ERwin Data Modeler r8.
She can be reached at
donna.burbank@globaldatastrategy.com
Donna is based in Boulder, Colorado,
USA.
2
Follow on Twitter @donnaburbank
3. Global Data Strategy, Ltd. 2016
Nigel Turner
Nigel has worked in Information Management
(IM) and related areas for over 20 years. This
experience has embraced Data Governance,
Information Strategy, Data Quality, Data
Governance, Master Data Management, &
Business Intelligence.
He spent much of his career in British
Telecommunications Group (BT) where he led
a series of enterprise wide IM initiatives
which brought huge benefits to BT. He also
created and led large IM & CRM consultancy
& delivery practices which served BT Global
Services’ customers.
After leaving BT in 2010 Nigel became VP of
Information Management Strategy at Harte
Hanks Trillium Software, a leading global
provider of Data Quality & Data Governance
tools and consultancy. Here he engaged with
over 150 customer organisations from all
parts of the globe, undertaking extensive
engagements with HSBC, Progress Software,
British Gas, HBOS, EDF Energy, Severn Trent
Water, British Airways, Telefonica O2 and
others.
Nigel is a well known thought leader in
Information Management and has run
tutorials and presented at many international
conferences. He also authored the Data
Quality Strategy module of the Institute of
Data Marketing’s Data Management Award.
Nigel is very active in professional Data
Management organisations and is an elected
Data Management Association (DAMA) UK
Committee member. He was the joint winner
of DAMA International’s 2015 Community
Award for the work he initiated and led in
setting up a mentoring scheme in the UK
where experienced DAMA professionals
coach and support newer data management
professionals.
He can be reached at:
nigel.turner@globaldatastrategy.com
Nigel is based in Cardiff, Wales in the UK.
3
Follow on Twitter @NigelTurner8
4. Global Data Strategy, Ltd. 2016
Lessons in Data Modeling Series
• July 28th Why a Data Model is an Important Part of your Data Strategy
• August 25th Data Modeling for Big Data
• September 22nd UML for Data Modeling – When Does it Make Sense?
• October 27th Data Modeling & Metadata Management
• December 6th Data Modeling for XML and JSON
4
This Year’s Line Up
5. Global Data Strategy, Ltd. 2016
Agenda
• Data Strategy & Data Modeling
• Top-Down Business Requirements
• Bottom-Up Technical Landscape
• Data Modeling with other Data Management Disciplines
• Summary & Questions
5
What we’ll cover today
7. Global Data Strategy, Ltd. 2016
Building an Enterprise Data Strategy
7
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
8. Global Data Strategy, Ltd. 2016
How can we Transform the Business through Data?
Optimization: Becoming a Data-Driven Company
• Making the Business More Efficient
• Better Marketing Campaigns
• Higher quality customer data, 360 view of customer, competitive info, etc.
• Better Products
• Data-Driven product development, Customer usage monitoring, etc.
• Better Customer Support
• Linking customer data with support logs, network outages, etc.
8
Transformative: Becoming a Data Company
• Changing the Business Model via Data – data becomes the product
• Monetization of Information: examples across multiple industries including:
• Telco: location information, usage & search data, etc.
• Retail: Click-stream data, purchasing patterns
• Social Media: social & family connections, purchasing trends &
recommendations, etc.
• Energy: Sensor data, consumer usage patterns, smart metering, etc.
9. Global Data Strategy, Ltd. 2016
Basic Definitions
9
Business & Data Strategies
A BUSINESS STRATEGY is a medium to long term business plan which
details the aims & objectives of a business and how it means to
achieve them.
A DATA STRATEGY is a medium to long term plan for the improvement,
management & exploitation of data across a business, and how it is
to be achieved.
10. Global Data Strategy, Ltd. 2016
Business & Data Strategy – the Interdependency
10
Business Strategy Data Strategy
Sets Requirements for
Informs & Guides
Business Strategy
11. Global Data Strategy, Ltd. 2016
How a Data Model Fits Within a Data Strategy
11
Data Governance
Focus
Business
Strategy
Business Data
Model
Business Goals &
key data needs
Data Definitions
‘As is’ Data
Baseline
‘To be’ Data
Intention
Data Strategy
Investment (time & resources)Priority
13. Global Data Strategy, Ltd. 2016
Levels of Data Modeling
13
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
14. Global Data Strategy, Ltd. 2016
Conceptual Data Model
• Communication & Definition Of Business Rules
15. Global Data Strategy, Ltd. 2016
Logical Data Model
• More Detailed, Normalized, Potential Pre-cursor To Physical Design
16. Global Data Strategy, Ltd. 2016
“Creative” Data Model for Business Audience
• Using a “graphical data model” is an intuitive way to show data entities and their relationships to
a business audience.
• It’s a helpful way to show how data fits into the “big picture” of the organization & helps it run
effectively.
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17. Global Data Strategy, Ltd. 2016
The Value of Whiteboarding
It’s often helpful to “whiteboard” data models with sticky notes
Policy
Account
Employee
18. Global Data Strategy, Ltd. 2016
Identify High-Priority Data Elements
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Align with Business Drivers
Launch of New Product – Marketing Campaign
requires better customer information
Customer
Product
Region Vendor
Partner
Identify Key
Business Drivers
Filter Data Elements
Aligned with Business
Drivers
Focus Governance &
Improvement Efforts
on Key Data
Targeted Projects to
Show Short-Term
Results
19. Global Data Strategy, Ltd. 2016
Data Definitions - why bother?
The Tower of Babel
“If as one people
speaking the same
language they have
begun to do this, then
nothing they plan to do
will be impossible for
them. Come, let us go
down and confuse their
language so they will not
understand each other.”
Genesis 11:1-9
20. Global Data Strategy, Ltd. 2016
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
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What is in a name?
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”?
21. Global Data Strategy, Ltd. 2016
Data Definitions – The Benefits
• Helps scope the data strategy to focus on the data objects / attributes
that really matter
• Supports the development and enforcement of data standards &
business rules
• Enables selective data quality scrutiny & monitoring
• Prioritizes data improvement activities
• Underpins business and IT impact analysis & change control
• Informs and improves design gateways and approvals
• Better legal & regulatory control, especially if combined with Data
Governance
• If published and communicated, helps to raise general awareness of the
importance of key data
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23. Global Data Strategy, Ltd. 2016
Data Modeling Creates an “Active Inventory” of Data Assets
• Know what data you have: Create a visual inventory of database systems
• Know what your data means: Communicate key business requirements between business and IT
stakeholders
• Support data consistency: Build consistent database structures & support data governance
initiatives
Sybase
MySQL
Oracle
Data Models
Teradata
Sybase
SQL
Server
DB2
Teradata
SQL
Server DB2
MySQLSQL
Azure
SQL
Azure
Oracle
24. Global Data Strategy, Ltd. 2016
Metadata Adds Context & Definition
• Metadata stored in data models provides valuable business & technical context.
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25. Global Data Strategy, Ltd. 2016
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)
25
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.
26. Global Data Strategy, Ltd. 2016
Data Lineage
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Customer Database
Oracle
Customer Database
SQL Server
Sales Database
DB2
Staging Area Data Warehouse
“Sales Amount”
Transformation Rules
(ETL)
• Data Lineage shows the source to target mapping, or provenance for information.
• For example, to understand how “Sales Amount” in a data warehouse is calculated, it is necessary to
understand where the data came from and how it was manipulated along the way.
• Many data modeling tools track this lineage through integration with ETL tools, or with internal mapping
functionality.
27. Global Data Strategy, Ltd. 2016
Data Model Design Layer Relationships
• Data model design layer mappings show the relationship between business terms and their
physical implementations on a database platform.
27
Showing Semantic Mapping
Conceptual
Logical
Physical
Business Concepts
Data Entities
Physical Tables
Client
Customer
DB2TeradataOracle
CUST CUSTOMER CTABLE_16
In a Conceptual data model, there may
be a concept called “Client” which is the
term businesspeople use to describe the
people they sell to and work with.
The Logical model might
use the term “Customer”
for that same concept.
Which may be implemented in a number
of physical tables with varying naming
conventions.
Conceptual
Logical
Physical
Business Concepts
Data Entities
Physical Tables
28. 28
Data Modeling with other
Data Management Disciplines
Supporting Enterprise Data
Initiatives
29. Global Data Strategy, Ltd. 2016
Data Modeling for Data Warehousing & Business Intelligence
• 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:
• Data Modeling is the “Intelligence behind Business Intelligence”
• Understand source and target data systems
• Define business rules
• Optimize data structures to align queries with reports
Show me all
customers by region
Source Systems
Relational Model
Dimensional Model
30. Global Data Strategy, Ltd. 2016
Data Modeling for Enterprise Architecture
• Enterprise Architecture provides a high-level view of the people, processes, applications, and data
of an organization
• Putting data in business context
• How does data link to the rest of my organization?
• If I change data, what business processes are affected?
31. Global Data Strategy, Ltd. 2016
Data Modeling for Cloud and SaaS
Cloud Database
DB2
Sybase
SQL Server
Teradata
Oracle
• A Data Model is your “roadmap” for:
What data to move to the Cloud, and what to keep on-premises
Defining data structures (physical model) and business requirements (logical model) for Cloud databases
• Off-Premises doesn’t mean Out of your Control
Data Model
32. Global Data Strategy, Ltd. 2016
Data Modeling for Application Development
• The majority of today’s applications are data-driven
• Data Modeling is a key part of the application development lifecycle
• Reuse of common data objects helps promote
• Increased efficiency – don’t “reinvent the wheel”
• Better collaboration
• Increased quality and consistency
33. Global Data Strategy, Ltd. 2016
Data Modeling for Master Data Management
• Master Data Management strives to create a “single version of the truth” for key business data:
customer, product, etc.
• Using a central data model helps define:
• Common business definitions
• Common data structures
• Data lineage between defined “version of the truth” and real-world implementations
34. Global Data Strategy, Ltd. 2016
Data Modeling for Data Governance
• Data, like money, is a corporate asset, and needs to be managed accordingly.
• Like an auditing department for finance, data governance provides the guidelines, accountability
and regulations around data management.
• Data Models can help define:
• What are the standards, domains, and rules for data?
• Who is accountable for data (e.g. Data Steward)?
• Who is using data?
• What is the lineage and traceability of data?
• What is the proper definition of key business information?
• When was the data last updated?
35. Global Data Strategy, Ltd. 2016
Data Modeling Supports an Enterprise Data Strategy
35
From Top-Down to Bottom-Up
Conceptual Data Model
Physical Data Model
• Data Lineage
• Impact Analysis
• Metadata Management
• Data Standards
• Etc.
Data Modeling Ecosystem
36. Global Data Strategy, Ltd. 2016
Summary
• Data Strategy & Data Modeling
• Top-Down Business Requirements
• Bottom-Up Technical Landscape
• Data Modeling with other Data Management Disciplines
• Summary & Questions
36
The Importance of Data Modeling to Data Strategy
37. Global Data Strategy, Ltd. 2016
About Global Data Strategy, Ltd.
• Global Data Strategy is an international information management consulting company specializing 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 technological solution.
• Clear & Relevant: We provide clear explanations using real-world examples, not technical jargon.
• 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, and we attract high-
quality professionals with years of technical expertise in the industry.
37
Data-Driven Business Transformation
Business Strategy
Aligned With
Data Strategy
38. Global Data Strategy, Ltd. 2016
Contact Info
• Email: donna.burbank@globaldatastrategy.com
nigel.turner@globaldatastategy.com
• Twitter: @GlobalDataStrat
@donnaburbank
@NigelTurner8
• Website: www.globaldatastrategy.com
• Company Linkedin: https://www.linkedin.com/company/global-data-strategy-ltd
• Personal Linkedin: https://www.linkedin.com/in/donnaburbank
https://uk.linkedin.com/in/nigelturnerdataman
38
DAMA Rocky Mountain Chapter
Website: http://www.dama-rockymountainchapter.org/
Twitter: @DAMA_RMC
DAMA UK Chapter
Website: http://www.damauk.org/
Twitter: @DAMAUK
39. Global Data Strategy, Ltd. 2016
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.
Use discount code “GDS” to receive 20% off!
• Register here
• Other courses available on Data Governance & Data Quality
39
Online Training Courses
New Metadata Management Course
Visit: http://training.dataversity.net/lms/
40. Global Data Strategy, Ltd. 2016
Lessons in Data Modeling Series
• July 28th Why a Data Model is an Important Part of your Data Strategy
• August 25th Data Modeling for Big Data
• September 22nd UML for Data Modeling – When Does it Make Sense?
• October 27th Data Modeling & Metadata Management
• December 6th Data Modeling for XML and JSON
40
Join us next month
41. Global Data Strategy, Ltd. 2016
Questions?
• Questions on Data Strategy & Data Modeling?
• Questions for next month’s topic on Big Data & Data Modeling?
• Suggestions for next year’s lineup?
41
Thoughts? Ideas?