This document outlines the top 10 best practices for successful master data management (MDM) implementations according to MDM experts. It discusses supporting multiple business data domains, automatically generating web services and user interfaces, starting small and scaling the implementation, creating a single best version of truth, and ensuring the MDM solution supports reference data needs. The document is presented by speakers from The MDM Institute and an MDM product marketing company.
Master Data Management – Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as customers, products, vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar will provide practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
Reference matter data management:
Two categories of structured data :
Master data: is data associated with core business entities such as customer, product, asset, etc.
Transaction data: is the recording of business transactions such as orders in manufacturing, loan and credit card payments in banking, and product sales in retail.
Reference data: is any kind of data that is used solely to categorize other data found in a database, or solely for relating data in a database to information beyond the boundaries of the enterprise .
Master Data Management – Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as customers, products, vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar will provide practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
Reference matter data management:
Two categories of structured data :
Master data: is data associated with core business entities such as customer, product, asset, etc.
Transaction data: is the recording of business transactions such as orders in manufacturing, loan and credit card payments in banking, and product sales in retail.
Reference data: is any kind of data that is used solely to categorize other data found in a database, or solely for relating data in a database to information beyond the boundaries of the enterprise .
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
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 identify the correct Master Data subject areas & tooling for your MDM...Christopher Bradley
1. What are the different Master Data Management (MDM) architectures?
2. How can you identify the correct Master Data subject areas & tooling for your MDM initiative?
3. A reference architecture for MDM.
4. Selection criteria for MDM tooling.
chris.bradley@dmadvisors.co.uk
Data Governance — Aligning Technical and Business ApproachesDATAVERSITY
Data Governance can have a varied definition, depending on the audience. To many, data governance consists of committee meetings and stewardship roles. To others, it focuses on technical data management and controls. Holistic data governance combines both of these aspects, and a robust data architecture and associated diagrams 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 & data governance for business and IT success.
Master Data Management's Place in the Data Governance Landscape CCG
For many organizations, Master Data Management is a necessity to ensure consistency and accuracy of essential business entities. It further plays alongside data architecture, metadata management, data quality, security & privacy, and program management in the Data Governance ecosystem.
Join CCG's data governance subject matter experts as they overview the fundamentals of Master Data Management at our Atlanta-based Data Analytics Meetup. This event will discuss how to enable components of data governance within your organization and review how to best leverage Microsoft's SQL Server Master Data Services.
This presentation reports on data governance best practices. Based on a definition of fundamental terms and the business rationale for data governance, a set of case studies from leading companies is presented. The content of this presentation is a result of the Competence Center Corporate Data Quality (CC CDQ) at the University of St. Gallen, Switzerland.
Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how Data Architecture is a key component of an overall Enterprise Architecture for enhanced business value and success.
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...DATAVERSITY
A solid data architecture is critical to the success of any data initiative. But what is meant by “data architecture”? Throughout the industry, there are many different “flavors” of data architecture, each with its own unique value and use cases for describing key aspects of the data landscape. Join this webinar to demystify the various architecture styles and understand how they can add value to your organization.
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
Enterprise Data World Webinars: Master Data Management: Ensuring Value is Del...DATAVERSITY
Now that your organization has decided to move forward with Master Data Management (MDM), how do you make sure that you get the most value from your investment? In this webinar, we will cover the critical success factors of MDM that ensure your master data is used across the enterprise to drive business value. We cover:
· The key processes involved in mastering data
· Data Governance’s role in mastering data
· Leveraging data stewards to make your MDM program efficient
· How to extend MDM from one domain to multiple domains
· Ensuring MDM aligns to business goals and priorities
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!
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.
Master Data Management - Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) can provide significant value to the organization in creating consistent key data assets such as Customer, Product, Supplier, Patient, and the list goes on. But getting MDM “right” requires a strategic mix of Data Architecture, business process, and Data Governance. Join this webinar to learn how to find the “sweet spot” between technology, design, process, and people for your MDM initiative.
Glossaries, Dictionaries, and Catalogs Result in Data GovernanceDATAVERSITY
Data catalogs, business glossaries, and data dictionaries house metadata that is important to your organization’s governance of data. People in your organization need to be engaged in leveraging the tools, understanding the data that is available, who is responsible for the data, and knowing how to get their hands on the data to perform their job function. The metadata will not govern itself.
Join Bob Seiner for the webinar where he will discuss how glossaries, dictionaries, and catalogs can result in effective Data Governance. People must have confidence in the metadata associated with the data that you need them to trust. Therefore, the metadata in your data catalog, business glossary, and data dictionary must result in governed data. Learn how glossaries, dictionaries, and catalogs can result in Data Governance in this webinar.
Bob will discuss the following subjects in this webinar:
- Successful Data Governance relies on value from very important tools
- What it means to govern your data catalog, business glossary, and data dictionary
- Why governing the metadata in these tools is important
- The roles necessary to govern these tools
- Governance expected from metadata in catalogs, glossaries, and dictionaries
Embarcadero Technologies & Ron Lewis, Senior Security Analyst with CDO Technologies hosted a live one hour webinar on the "Five Steps to Mastering Master Data Management. Learn how a solid metadata repository can support data governance and increase the effectiveness of master data use.
The what, why, and how of master data managementMohammad Yousri
This presentation explains what MDM is, why it is important, and how to manage it, while identifying some of the key MDM patterns and best practices that are emerging. This presentation is a high-level treatment of the problem space.
The presentation is summarizing the article of Microsoft in a simple way.
https://msdn.microsoft.com/en-us/library/bb190163.aspx
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
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 identify the correct Master Data subject areas & tooling for your MDM...Christopher Bradley
1. What are the different Master Data Management (MDM) architectures?
2. How can you identify the correct Master Data subject areas & tooling for your MDM initiative?
3. A reference architecture for MDM.
4. Selection criteria for MDM tooling.
chris.bradley@dmadvisors.co.uk
Data Governance — Aligning Technical and Business ApproachesDATAVERSITY
Data Governance can have a varied definition, depending on the audience. To many, data governance consists of committee meetings and stewardship roles. To others, it focuses on technical data management and controls. Holistic data governance combines both of these aspects, and a robust data architecture and associated diagrams 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 & data governance for business and IT success.
Master Data Management's Place in the Data Governance Landscape CCG
For many organizations, Master Data Management is a necessity to ensure consistency and accuracy of essential business entities. It further plays alongside data architecture, metadata management, data quality, security & privacy, and program management in the Data Governance ecosystem.
Join CCG's data governance subject matter experts as they overview the fundamentals of Master Data Management at our Atlanta-based Data Analytics Meetup. This event will discuss how to enable components of data governance within your organization and review how to best leverage Microsoft's SQL Server Master Data Services.
This presentation reports on data governance best practices. Based on a definition of fundamental terms and the business rationale for data governance, a set of case studies from leading companies is presented. The content of this presentation is a result of the Competence Center Corporate Data Quality (CC CDQ) at the University of St. Gallen, Switzerland.
Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how Data Architecture is a key component of an overall Enterprise Architecture for enhanced business value and success.
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...DATAVERSITY
A solid data architecture is critical to the success of any data initiative. But what is meant by “data architecture”? Throughout the industry, there are many different “flavors” of data architecture, each with its own unique value and use cases for describing key aspects of the data landscape. Join this webinar to demystify the various architecture styles and understand how they can add value to your organization.
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
Enterprise Data World Webinars: Master Data Management: Ensuring Value is Del...DATAVERSITY
Now that your organization has decided to move forward with Master Data Management (MDM), how do you make sure that you get the most value from your investment? In this webinar, we will cover the critical success factors of MDM that ensure your master data is used across the enterprise to drive business value. We cover:
· The key processes involved in mastering data
· Data Governance’s role in mastering data
· Leveraging data stewards to make your MDM program efficient
· How to extend MDM from one domain to multiple domains
· Ensuring MDM aligns to business goals and priorities
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!
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.
Master Data Management - Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) can provide significant value to the organization in creating consistent key data assets such as Customer, Product, Supplier, Patient, and the list goes on. But getting MDM “right” requires a strategic mix of Data Architecture, business process, and Data Governance. Join this webinar to learn how to find the “sweet spot” between technology, design, process, and people for your MDM initiative.
Glossaries, Dictionaries, and Catalogs Result in Data GovernanceDATAVERSITY
Data catalogs, business glossaries, and data dictionaries house metadata that is important to your organization’s governance of data. People in your organization need to be engaged in leveraging the tools, understanding the data that is available, who is responsible for the data, and knowing how to get their hands on the data to perform their job function. The metadata will not govern itself.
Join Bob Seiner for the webinar where he will discuss how glossaries, dictionaries, and catalogs can result in effective Data Governance. People must have confidence in the metadata associated with the data that you need them to trust. Therefore, the metadata in your data catalog, business glossary, and data dictionary must result in governed data. Learn how glossaries, dictionaries, and catalogs can result in Data Governance in this webinar.
Bob will discuss the following subjects in this webinar:
- Successful Data Governance relies on value from very important tools
- What it means to govern your data catalog, business glossary, and data dictionary
- Why governing the metadata in these tools is important
- The roles necessary to govern these tools
- Governance expected from metadata in catalogs, glossaries, and dictionaries
Embarcadero Technologies & Ron Lewis, Senior Security Analyst with CDO Technologies hosted a live one hour webinar on the "Five Steps to Mastering Master Data Management. Learn how a solid metadata repository can support data governance and increase the effectiveness of master data use.
The what, why, and how of master data managementMohammad Yousri
This presentation explains what MDM is, why it is important, and how to manage it, while identifying some of the key MDM patterns and best practices that are emerging. This presentation is a high-level treatment of the problem space.
The presentation is summarizing the article of Microsoft in a simple way.
https://msdn.microsoft.com/en-us/library/bb190163.aspx
PC Management, MAM, MDM, EMM, Data and Files Management, Identity Management....Microsoft Technet France
Présentation des facteurs de différenciation de Microsoft par rapport à la concurrence, en ce qui concerne la gestion des PC, des périphériques mobiles et autres périphériques modernes mais aussi en ce qui concerne la gestion et la protection des applications (SaaS ou non), ou encore la gestion et la protection des données et des identités.
informatica mdm training | best informatica mdm Online training - GOTGlobal Online Trainings
informatica mdm training course is a unique framework delivers consolidated and reliable business data .Signup for siperian mdm online training study material
Unlocking Success in the 3 Stages of Master Data ManagementPerficient, Inc.
Master data management (MDM) comprises the processes, governance, policies, standards and tools that define and manage critical data. MDM is used to conduct strategic initiatives such as customer 360, product excellence and operational efficiency.
The quality of enterprise Information depends on the master data, so getting it right should be a high priority. This webinar will highlight key factors needed for success in each of the three stages of the MDM journey:
Planning
Implementation
Steady state
We review each stage in detail and provide insight into planning and collaborative activities. In this slideshare you will learn:
Best practices, tips and techniques for a successful MDM program
Top considerations for business case building, architecture and going live
How to support the overall program after launching your MDM program
Informatica mdm online training in India,Informatica mdm online training in USA,Informatica mdm online training in UK,Informatica mdm online training in Canada
Mike Ferguson, managing director of Intelligent Business Strategies, highlights his top ten worst practices in Master Data Management (MDM) in this Information Builders webinar slideshow.
Le 16 octobre j’ai assisté à une conférence organisée par information builders au Shangri la de Paris intitulée : « Les nouveaux enjeux de l’EIM, MDM et big data, l’association gagnante ». Même si le titre est un peu abscons, et requiert lui-même un peu de data mining, le contenu allait au-delà de mes espérances avec une présentation très intéressante de Jean-Michel Franco (photo), Directeur de l’innovation chez Business & décision. Et je peux dire qu’enfin j’ai tout compris, ou presque,au big data, au vrai big data, pas aux incantations aux dieux de la mode, mais à la description d’une vraie révolution au sein des entreprises et des directions marketing qui n’a pas fini de créer des remous dans les organisations et les méthodologies. Voir mon compte-rendu : http://wp.me/p3XOzT-2wS
Presentation of the Gradoop Framework at the Flink & Neo4j Meetup in Berlin (http://www.meetup.com/graphdb-berlin/events/228576494/). The talk is about the extended property graph model, its operators and how they are implemented on top of Apache Flink. The talk also includes some benchmark results on scalability and a demo involving Neo4j, Flink and Gradoop (see www.gradoop.com)
Raphael Colsent describes National Bank's path to implementing their enterprise-wide MDM. National Bank is mastering data from over 500 domains and supporting their Basel II, CRM, and BI applications with EBX5.
Reference:
Colsenet, Raphael "National Bank MDM Initiative,"
Presentation from 2011 MDM and Data Governance Summit in Toronto, Canada, June 2011.
Conference Chairman Keynote & Welcome
Capitalizing on MDM in Times of Crisis
Aaron Zornes, Founder & Chief Research Officer, The MDM Institute
--------------------------------------------------------------------------------
MDM is particularly important in today’s increasingly complex and harsh global business landscape – in part due to increasingly demanding suppliers, trading partners, customers … as well as financial challenges and government regulations. Despite the current economic crisis, analyst firms have declared MDM to be “recession proof” as businesses strive to dramatically reduce costs, meet compliance reporting mandates, deliver increased sales and marketing effectiveness, and provide superior service to customers and suppliers. MDM and its variants – customer data integration (CDI), product information management (PIM), and data governance – all significantly contribute to these tactical business priorities.
Research analysts at the MDM Institute annually produce a set of twelve milestones for their MDM Road Map to help Global 5000 enterprises focus efforts for their own large-scale, mission-critical MDM projects. This keynote will focus on this set of strategic planning assumptions and present an enlightening view of the key trends and issues facing IT organizations during 2009-10 and beyond by highlighting:
Understanding the impact of MDM market momentum, maturation, and consolidation
Coping with the skills shortage for data governance, MDM project leadership, & enterprise architecture
Identifying the essential (vs. desirable) features of an enterprise-strength MDM solution
DMA 2014: 6 Steps to Integrate Your Big DataSameer Khan
The Big Data phenomenon was all about the collection of masses and masses of data: it was a technology challenge. But for most of us, this is no longer a problem – we know how to collect the data – the challenge now is one of processing the data, to make smart data work for us. In this session, IBM’s Sameer Khan will outline an action plan to manage your data and make it smart. He will be ably supported by Andrew Bailey, who will bring his experience with using smart data for integrated marketing campaigns to show you how it is put into action at a company like FedEx.
Analyst field reports on top 20 MDM and Data Governance implementation partne...Aaron Zornes
(1) Determining the evaluation criteria for selecting implementation partners for MDM, RDM and Data Governance projects
(2) Identifying which partners are market leaders in your industry & your chosen software technologies
(3) Managing the partner relationship – esp. avoiding “brain drain” & inflationary “blended rates”
Analyst field reports on top 10 data governance solutions - Aaron Zornes (NYC...Aaron Zornes
All you need to know to understand the "data governance" market -- which business uses cases and technology are key, and which solution providers (software & services) are essential
Poor data quality should be a primary driver in selecting and implementing a Master Data Management solution, and yet 64% of organizations say it's the reason they abandoned the evaluation.*
*Profisee Topline Market Study 2020
Making Information Management The Foundation Of The Future (Master Data Manag...William McKnight
More complex and demanding business environments lead to more heterogeneous systems environments. This, in turn, results in requirements to synchronize master data. Master Data Management (MDM) is an essential discipline to get a single, consistent view of an enterprise\’s core business entities – customers, products, suppliers, and employees. MDM solutions enable enterprise-wide master data synchronization. Given that effective master data for any subject area requires input from multiple applications and business units, enterprise master data needs a formal management system. Business approval, business process change, and capture of master data at optimal, early points in the data lifecycle are essential to achieving true enterprise master data.
Data Ownership:
Most companies and organizations have this notion that data governance should be taken care of ,
by the Information Technology department, because IT owns the system which stores the data.
The owner of the data is responsible for providing attributes to the data and answerable to any questions regarding data.
The people answerable to these kinds of data are generally the ones involved in defining business rules,
data cleaning and consolidation.?
Data Stewardship:?
Data stewards should be favorably those people who are familiar with the data. It is often seen that
there is need to deploy several people, to handle and correct data,
whereas a single data steward could have done the same job. Since the data being handled involves
organizational level data, it is important that there are governance rules for this process.?
If there is some certain rule in the data which causes large data volumes to fail, this rule should be fixed while data cleansing.
So it is important to take care of the amount of clean data sent to the stewards,
since we are not aware of which rules might trigger what amount of data.?
Choice of data stewards is again a difficult selection.
Data Security:?
Although the master data is data on organization level, but there is some confidentiality level linked to it.?
Not every employee has the authorization to view its aspects.
Security rules can be applied to the data.
The various departments in the organization must set different rules to the data they own.
They need to grant permissions to these rules , so that the user can view the data.
A large company can have data sourced out of many regions.
It is to be ensured that they are responsible to correct only their own data.?
Data survivorship:
There are some guidelines which are set up by data governance.
These rules can often change over hthe time according to new data sources being added.
The changes made to the data , are communicated to the organization so that data stewards and users can understand the process.
So from a data steward's point of view, it is important to apply security rules to the people who are involved
in data handling and correction. This is a result of how data governance and data security can be applied while implementing MDM.?
?
Big Data Management: A Unified Approach to Drive Business ResultsCA Technologies
Traditional data management is changing rapidly, attributed to significant changes brought on by evolving big data environments. IT complexity is on the rise as businesses choose the technologies they need to support their big data strategies and targeted business outcomes. Now, more than ever, we need IT management tools that can accommodate and effectively manage these evolving, complex environments to ensure that enterprises can move forward with their preferred technology and vendor choices.
For more information on Mainframe solutions from CA Technologies, please visit: http://bit.ly/1wbiPkl
Similar to Informatica Presents: 10 Best Practices for Successful MDM Implementations from MDM Experts (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.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
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.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
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!
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.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
JMeter webinar - integration with InfluxDB and Grafana
Informatica Presents: 10 Best Practices for Successful MDM Implementations from MDM Experts
1. “Top 10” Best Practices
for Successful MDM Implementations
from MDM Experts
11-Oct-2012
Presented by:
1
2. Speakers
Aaron Zornes Ravi Shankar
Chief Research Officer Vice President
The MDM Institute MDM Product Marketing
3. “Top 10” Best Practices
1. Support Multiple 6. Integrate Flexible
Business Data Master Data
Domains Governance
2. Automatically 7. Plan Multiple
Generate Web Deployment Modes
Services, UI 8. Integrate Social
3. Start Small & Scale Data
4. Create Best Version 9. Enable Mobile MDM
of Truth 10.Leverage Big Data
5. Support Reference MDM
Data Management
The MDM Institute www.The-MDM-Institute.com
4. 1. Support Multiple Business Data
Domains
Through 2012, corporate MDM platform evaluation
teams will assume (and insist) that all MDM software
platforms targeted for enterprise-level deployment or
major role in mission-critical systems fully support both
PARTY & THING entity types
By 2015, all operational CDI hub vendors will add "PIM
light" capabilities, and all PIM vendors will add B2C
PARTY entity
MDM MILESTONE
The MDM Institute www.The-MDM-Institute.com
5. 1. Support Multiple Business Data
Domains With a Flexible Data Model
Through 2012, corporate MDM platform evaluation
teams will assume (and insist) that all MDM software
platforms targeted for enterprise-level deployment or
major role in mission-critical systems fully support both
PARTY & THING entity types
By 2015, all operational CDI hub vendors will add "PIM
light" capabilities, and all PIM vendors will add B2C
PARTY entity
Customer Data Affiliation Data Product Data List Prices and
(April 2007) (December 2007) (Med Devices) Sales Alignment Data
(January 2008) (Med Devices) (July 2008)
Flexible Multidomain Data Model Allows You To: Adapts to
• Adapt to your business requirements and data model Your
DATA
• Does not force you to adapt to fixed, vendor-defined data model
MDM MILESTONE
The MDM Institute www.The-MDM-Institute.com
6. Poll Question #1: Please respond now!
For your current MDM project, are you planning to
master one data domain or many?
• One
• Two
• Three or more
• Don’t know yet
6
7. 2. Automatically Generate Web
Services and UI Elements
Generate granular web services automatically and create
higher-level composite services for rapid integration
Generate UI elements automatically from data model
definitions
Reuse business rules across unified MDM, data integration
and data quality on a single platform
The MDM Institute www.The-MDM-Institute.com
8. 2. Automatically Generate Web
Services and UI Elements
Generate granular web services automatically and create
higher-level composite services for rapid integration
Generate UI elements automatically from data model
definitions
Reuse business rules across unified MDM, data integration
and data quality on a single platform
Customer Product
Organization
Data Model Services User Interface
Automatically Generated Services and User Interface: Adapts to
• Delivers value in weeks in every phase of your project Your
PROJECT
• Does not delay your project to years and risk cancellation
The MDM Institute www.The-MDM-Institute.com
9. 3. Start Small and Scale
Extend the data model to include any other data domains
and solutions
Regenerate services
Configure workflow to adapt to increased data governance
scope
Better interoperability with existing architecture
The MDM Institute www.The-MDM-Institute.com
10. 3. Start Small and Scale with a
Platform Approach to MDM
Extend the data model to include any other data domains
and solutions
Regenerate services
Configure workflow to adapt to increased data governance
scope
Better interoperability with existing architecture
3
2
1
Using same platform to scale to other business problems: Adapts to
• Leverages your existing investments as business needs evolve Your
BUSINESS
• Does not increase your TCO by requiring additional MDM apps
The MDM Institute www.The-MDM-Institute.com
11. Poll Question #2: Please respond now!
Is it important for you to be able to use your own
data models or industry-specific data models?
• Use my own data model
• Use industry-specific data model
• Use a combination of the two
• Not sure yet
11
12. 4. Create Best Version of Truth
Consolidate duplicate data into best version of the truth
(BVT)
MDM vendors will make available multiple BVT to support
the needs of different business users – marketing, sales,
finance, etc.
Through 2012, registry-style MDM solutions will find favor
in industries where data is legally or physically too difficult
to consolidate into physical hub -- esp. government, US
healthcare)
MDM MILESTONE
The MDM Institute www.The-MDM-Institute.com
13. 4. Create Best Version of Truth With
Cell-Level Merge
Consolidate duplicate data into best version of the truth
(BVT)
MDM vendors will make available multiple BVT to support
the needs of different business users – marketing, sales,
finance, etc.
Through 2012, registry-style MDM solutions will find favor
Master Record
in industries where data is legally or physically too difficult
to consolidate into physical hub -- esp. government, US
Party Name Public Domicil Industr As of Date Total Assets Liquid Assets Equity Credit Rating
e y
IXIS Corporate & Investment Y 1/31/2006 $207,059 $190,157 $3,342 AAA-
healthcare) Bank
UnionBanCal
Y
France
USA
6021
6021
3/27/2006 $207,059 $190,157 $3,342 AA-
Y 4/15/2006 $481,741 $383,522 $40,666 AAA
General Electric Company USA 3511
Name_Full SWIFT # ADDR1 CITY ADDR4 ADDR5 COUNTRY
Union Bank of California 308-03-8500 Elm and Carlton Streets Minneapolis MN 50423 USA
General Electric Company 005-10-4640 123 Main Street New Haven CT 14263 USA
IXIS Corporate & Investment Bank 917-13-8500 57, rue du Foubourg Paris 75003 France
CRM
MDM MILESTONE
The MDM Institute www.The-MDM-Institute.com
14. 5. Ensure MDM Supports Your
Reference Data Needs
During 2012-13, reference data will emerge as a key
entry point for enterprises & in turn influence choice of
MDM for Customer, Product & other domains
Concurrently, every MDM vendor will rush to market
RDM solutions to apply MDM approach for centralized
governance, stewardship & control
By 2013-14, large enterprises will also mandate that
Reference Data be part of MDM platform native entities
MDM MILESTONE
The MDM Institute www.The-MDM-Institute.com
15. 5. Ensure MDM Supports Your
Reference Data Needs
During 2012-13, reference data will emerge as a key
entry point for enterprises & in turn influence choice of
MDM for Customer, Product & other domains
Concurrently, every MDM vendor will rush to market
RDM solutions to apply MDM approach for centralized
governance, stewardship & control
By 2013-14, large enterprises will also mandate that
Reference Data be part of MDM platform native entities
Nonprofit healthcare provider uses multidomain master
data management (MDM) to create single source of
ICD-10 master data, streamline reimbursements, and
maximize return on data.
MDM MILESTONE
The MDM Institute www.The-MDM-Institute.com
16. 6. Integrate Flexible Master Data
Governance
Through 2012, most enterprises will struggle with
enterprise MDG as they initially focus on customer,
vendor, or product; integrated MDG that includes E2E
data lifecycle will be mandated as 1st phase deliverable
By 2014-15, vendor MDM solutions will finally move from
“passive-aggressive MDG” mode to “proactive MDG”
MDM MILESTONE
The MDM Institute www.The-MDM-Institute.com
17. 6. Integrate Flexible Master Data
Governance
Through 2012, most enterprises will struggle with
enterprise MDG as they initially focus on customer,
vendor, or product; integrated MDG that includes E2E
data lifecycle will be mandated as 1st phase deliverable
By 2014-15, vendor MDM solutions will finally move from
“passive-aggressive MDG” mode to “proactive MDG”
Customer
Order Entry
and Informatica
Affiliation Data MDM
Master Data Steward
(Data Owner) System of
Contracting Record
MDM MILESTONE
The MDM Institute www.The-MDM-Institute.com
18. 7. Plan to Deploy Multiple Modes –
On-premise, Cloud, Hybrid
During 2012, cloud-enabled MDM will attract small- &
mid-sized businesses as a means to engage in MDM
Through 2013-14, cloud-integrated apps arrive via SFDC,
however, enterprises will wrestle with data integration
issues between on-premise & cloud
By 2014-15, cloud-innate services for DQ & MDG will be
more prevalent; however, Enterprise MDM will remain
“on premise” with increasing integration to public Cloud
applications
MDM MILESTONE
The MDM Institute www.The-MDM-Institute.com
19. 7. Plan to Deploy Multiple Modes –
On-premise, Cloud, Hybrid
During 2012, cloud-enabled MDM will attract small- &
mid-sized businesses as a means to engage in MDM
Through 2013-14, cloud-integrated apps arrive via SFDC,
however, enterprises will wrestle with data integration
issues between on-premise & cloud
By 2014-15, cloud-innate services for DQ & MDG will be
On-premise MDM
more prevalent; however,multidomain, anyMDM willtarget, operational
• For
Enterprise source, any remain
“on premise” with increasing integration to public Cloud
and analytical use cases
applications MDM as a Service – Cloud MDM
On premise Cloud
• For Salesforce.com
Hybrid MDM – On-premise / Cloud
Hybrid • Support cross-enterprise, cross-instance business
MDM MILESTONE processes
The MDM Institute www.The-MDM-Institute.com
20. 8. Plan to integrate Social Data
MDM maintaining the master customer profile data will be
key integration point btwn Social CRM & big data analytics
During 2012, businesses will evaluate integration of social
data for sales, marketing, and support processes; use
MDM for identity resolution
Through 2013-14, MDM, data integration enabling social
data arrive via Facebook apps, Twitter, etc.; Enterprises
will begin integrating social data with on-premise CRM,
SFDC
MDM MILESTONE
The MDM Institute www.The-MDM-Institute.com
21. 8. Plan to integrate Social Data to
Gain Complete Customer View
MDM maintaining the master customer profile data will be
key integration point btwn Social CRM & big data analytics
During 2012, businesses will evaluate integration of social
data for sales, marketing, and support processes; use
MDM for identity resolution
Through 2013-14, MDM, data integration enabling social
data arrive via FacebookDeeper understanding of
apps, Twitter, etc.; Enterprises
will begin integrating social data with on-premise CRM,
customer likes and dislikes
SFDC View social graph; understand
network of influence
Track social interactions
about product and company
MDM MILESTONE
The MDM Institute www.The-MDM-Institute.com
22. 9. Enable Mobile MDM for the Sales
Force
During 2012-13, Businesses are arming business users
with mobile devices for increased productivity and
mobility; Business users access master data “on the go”,
where ever they are
By 2013-14, Mobile MDM needs to support location-
based services and available on iOS and Android devices
The MDM Institute www.The-MDM-Institute.com
23. 9. Enable Mobile MDM for the Sales
Force With Mobile MDM App
During 2012-13, Businesses are arming business users
with mobile devices for increased productivity and
mobility; Business users access master data “on the go”,
where ever they are
By 2013-14, Mobile MDM needs to support location-
based services and available on iOS and Android devices
Enable the Mobile workforce
• See location-based view of the customer
• View customer Transaction and Social
Data
The MDM Institute www.The-MDM-Institute.com
24. 10. Leverage Big Data for Very Large
Data Sets
During 2012, performance of all major aspects of base
MDM functionality will benefit from performance-
enhancing capabilities of big memory configurations —
from batch loading of MDM hubs to identity resolution to
operational updates
Through 2013, big data will repatriate itself into the MDM
fabric via registry overlays as yet another source
By 2014-15, very large enterprises (fin svcs, gov’t) will
be looking for real-time MDM flows & scaling of MDM
solutions via the elasticity of Cloud-based solutions, in-
memory cache databases, i.e., the next-generation of
ETL/MDM
MDM MILESTONE
The MDM Institute www.The-MDM-Institute.com
25. 10. Leverage Big Data for Very Large
Data Sets
During 2012, performance of all major aspects of base
MDM functionality will benefit from performance-
enhancing capabilities of big memory configurations —
from batch loading of MDM hubs to identity resolution to
operational updates
Through 2013, big data will repatriate itself into the MDM
fabric via registry overlays as yet another source
Intelligence
2 Billion
By 2014-15, very large enterprises Hadoop (or similar) will
Agency • Leverage (fin svcs, gov’t)
be looking for real-time MDM Big Data& scaling entity resolution
Search Engine infrastructure to solve
flows of MDM
Records
Company Credit in
solutions via the elasticity of Cloud-based solutions, in-
Bureau
Large batch deduplication
memory cache databases, •i.e., the next-generation of
ETL/MDM • Social Media analysis
Velocity
MDM MILESTONE
The MDM Institute www.The-MDM-Institute.com
26. Next Steps
Download Demo Ask Questions
Flexible Business-Model Driven MDM Informatica MDM LinkedIn Group
Aaron Zornes Ravi Shankar
Founder & Chief Research Officer VP, MDM Product Marketing
The MDM Institute Informatica
www.the-MDM-Institute.com www.informatica.commdm
aaron.zornes@tcdii.com RaShankar@informatica.com
@azornes @Ravi_Shankar_
26
27. MDM & Data Governance Summit Conferences
MDM & Data Governance Summit New York
Marriott Marquis NYC Times Square ▪ October 14-16
MDM & Data Governance Summit Americas
Marriott Marquis NYC Times Square ▪ October 14-16
MDM & Data Governance Summit Singapore
Marina Bay Sands Resort ▪ December 4-5
MDM & Data Governance Summit Shanghai
Shanghai International Convention Center ▪ March 2013
MDM & Data Governance Summit Europe
Radisson BLU – London ▪ April 15-17-15, 2013
MDM & Data Governance Summit Asia-Pacific
Four Points Darling Harbour– Sydney ▪ May 20-21, 2013
MDM & Data Governance Tokyo
Belle Salle Kanda– Tokyo ▪ June 14, 2013
MDM & Data Governance Summit San Francisco
Hyatt Embarcadero – San Francisco ▪ June 2013
MDM & Data Governance Summit Canada
The Carlu – Toronto ▪ June 27-28
“More MDM programs get their successful start at MDM
& Data Governance Summits than anywhere else”
27