CDO Webinar: Metadata and the CDO
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Thanks to wiki leaks, the NSA and intense regulatory environments, metadata is now a common term. What is the role of the Top Data Job and what are the options to deploy an effective metadata environment. John will explore some new avenues and lessons learned for metadata. In this webinar, we will discuss: Metadata Architectures Metadata Types and Categories Trends in Metadata Technology The CDO’s role in the Metadata Function
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How change management can enable the success of your data governance, reporting and analytics initiatives.
Common people change related challenges that many data governance, reporting and analytics initiatives need to navigate.
Change management techniques you can use to drive successful project delivery, change adoption and sustainable use of data governance, and reporting and analytics solutions.
How to identify the top change management priority for your own current project, and the change management techniques that you can use to address it.
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Mary is the founder of Sierra Creek Consulting
What Data Do You Have and Where is It?
Joe Caserta, President at Caserta Concepts presented at the 3rd Annual Enterprise DATAVERSITY conference. The emphasis of this year's agenda is on the key strategies and architecture necessary to create a successful, modern data analytics organization.
Joe Caserta presented What Data Do You Have and Where is it?
For more information on the services offered by Caserta Concepts, visit out website at http://casertaconcepts.com/.
Business Intelligence Priorities, Products and Services required in Enterprise
Salient BI concepts, popular products, typical services required to create a robust information management strategy in an organization. The document also talks about the various components of a BI environment present in an organization
20150118 s snet analytics vca
The document discusses the growing importance and opportunities of analytics for businesses. It notes that there is a widening performance gap between top performers and bottom performers in their use of data and analytics. While the amount of data is growing exponentially, there is also a significant skills gap in having enough talent to effectively analyze and use data. The document outlines several major themes where businesses are applying analytics, including customer insights, risk management, operations, and product design. It argues that analytics can drive significant business value when integrated into operations and transformations.
Intelligent Compliance to Optimize Energy Sector Enterprise Content Managemen...
Intelligent Compliance to Optimize Energy Sector Enterprise Content Managemen...Concept Searching, Inc
We explored how SharePoint can be enhanced to establish an ECM framework that ensures the availability, usability, integrity, and security of an enterprise’s information, and enables information consumers to:
• Find trusted and relevant information regarding health and safety, asset maintenance, and compliance guidelines such as OSHA, for key information for decision making
• Ensure accurate records management, regulatory compliance, and improve eDiscovery, and litigation support processes
• Identify and secure potential confidential or sensitive information exposures
• Rapidly address unexpected failures in processes, such as pipeline leaks or natural disasters
• Enable multinational content asset protection and authorization to assets
• Automate application and enforcement of policies
• Quickly react to deploy project-based hybrid cloud and on-premise collaborative solutionsDeliveinrg explainable AI
A lack of trust is inhibiting the adoption of #AI. This presentation discusses approaches to delivering trusted data pipelines for AI and machine learning
Using information management to support data driven actions
Traditional SQL and modern NoSQL data management technologies can transform the way we make our decisions.
You Need a Data Catalog. Do You Know Why?
Data catalog has become a more popular discussion topic within data management and data governance circles. “What is it?” and “Do I need one?” are two common questions; along with “How does a catalog relate to and support the data governance program?”
The data catalog plays a key role in the governance process: how well information can be managed, aligned to business objectives and monetized depends in great part to what you know about your data.
In this webinar you will learn about:
• The role of the data catalog
• What kinds of information should be in your data catalog
• Those catalog items that can be harvested systemically versus those that require stewardship involvement
• The role of the catalog in your data quality program
We hope you’ll join us and learn how a data catalog should be part of your governance and data quality program!
You Need a Data Catalog. Do You Know Why?
Data catalog has become a more popular discussion topic within data management and data governance circles. “What is it?” and “Do I need one?” are two common questions; along with “How does a catalog relate to and support the data governance program?”
The data catalog plays a key role in the governance process; How well information can be managed, aligned to business objectives and monetized depends in great part to what you know about your data.
In this webinar you will learn about:
- The role of the data catalog
- What kinds of information should be in your data catalog
- Those catalog items that can be harvested systemically versus those that require stewardship involvement
- The role of the catalog in your data quality program
We hope you’ll join this on-demand webinar and learn how a data catalog should be part of your governance and data quality program!
An Introduction to Advanced analytics and data mining
This presentation introduces the basic ideas of advanced analytics, data mining and the data mining process
You Need a Data Catalog. Do You Know Why?
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, and 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 webinar to learn more about the data catalog and its role in data governance efforts.
During this webinar, industry experts will cover:
• 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
The webinar will be led by industry experts including:
• Chris Reed, Manager, Sales Engineering, Precisely
• Matthew Vandevere, VP, Strategic Services, Precisely
• Colin Gibson, Moderator, Senior Advisor of DCAM & CDMC, EDM Council
DataEd Slides: Unlock Business Value Using Reference and Master Data Manageme...
Data tends to pile up and can be rendered unusable or obsolete without careful maintenance processes. Reference and Master Data Management (MDM) has been a popular Data Management approach to effectively gain mastery over not just the data but the supporting architecture for processing it from a master/transaction perspective. This webinar presents MDM as a strategic approach to improving and formalizing practices around those data items that provide context for organizational transactions – its master data. Too often, MDM has been implemented technology-first and achieved the same very poor track record (1/3 succeeding on-time, within budget, achieving planned functionality). MDM success depends on a coordinated approach involving typically Data Governance and Data Quality activities. Program learning objectives include:
• Understanding foundational reference and MDM concepts
• Why they are an important component of your Data Architecture
• Awareness of Reference and MDM Frameworks and building blocks
• What consists of MDM guiding principles and best practices
• How to utilize Reference and MDM in support of business strategy
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Fuel your Data-Driven Ambitions with Data Governance
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Enterprise Data Governance for Financial Institutions
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Operationalize analytics through modern data strategy
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Stop the madness - Never doubt the quality of BI again using Data Governance
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Business Intelligence Priorities, Products and Services required in Enterprise
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Intelligent Compliance to Optimize Energy Sector Enterprise Content Managemen...
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Using information management to support data driven actions
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An Introduction to Advanced analytics and data mining
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DataEd Slides: Unlock Business Value Using Reference and Master Data Manageme...
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More from DATAVERSITY
Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...
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 Governance
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.
Exploring Levels of Data Literacy
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 Goals
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.
Make Data Work for You
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?
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?
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
Data Modeling Fundamentals
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
Showing ROI for Your Analytic Project
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 Scale
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.
Is Enterprise Data Literacy Possible?
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...
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?
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 Forwards
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 Today
1) The document discusses best practices for data protection on Google Cloud, including setting data policies, governing access, classifying sensitive data, controlling access, encryption, secure collaboration, and incident response.
2) It provides examples of how to limit access to data and sensitive information, gain visibility into where sensitive data resides, encrypt data with customer-controlled keys, harden workloads, run workloads confidentially, collaborate securely with untrusted parties, and address cloud security incidents.
3) The key recommendations are to protect data at rest and in use through classification, access controls, encryption, confidential computing; securely share data through techniques like secure multi-party computation; and have an incident response plan to quickly address threats.
2023 Trends in Enterprise Analytics
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.
Data Strategy Best Practices
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?
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
Data Management Best Practices
This document summarizes a research study that assessed the data management practices of 175 organizations between 2000-2006. The study had both descriptive and self-improvement goals, such as understanding the range of practices and determining areas for improvement. Researchers used a structured interview process to evaluate organizations across six data management processes based on a 5-level maturity model. The results provided insights into an organization's practices and a roadmap for enhancing data management.
MLOps – Applying DevOps to Competitive Advantage
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.
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L'indice de performance des ports à conteneurs de l'année 2023
Une évaluation comparable de la performance basée sur le temps d'escale des navires
L'objectif de l'ICPP est d'identifier les domaines d'amélioration qui peuvent en fin de compte bénéficier à toutes les parties concernées, des compagnies maritimes aux gouvernements nationaux en passant par les consommateurs. Il est conçu pour servir de point de référence aux principaux acteurs de l'économie mondiale, notamment les autorités et les opérateurs portuaires, les gouvernements nationaux, les organisations supranationales, les agences de développement, les divers intérêts maritimes et d'autres acteurs publics et privés du commerce, de la logistique et des services de la chaîne d'approvisionnement.
Le développement de l'ICPP repose sur le temps total passé par les porte-conteneurs dans les ports, de la manière expliquée dans les sections suivantes du rapport, et comme dans les itérations précédentes de l'ICPP. Cette quatrième itération utilise des données pour l'année civile complète 2023. Elle poursuit le changement introduit l'année dernière en n'incluant que les ports qui ont eu un minimum de 24 escales valides au cours de la période de 12 mois de l'étude. Le nombre de ports inclus dans l'ICPP 2023 est de 405.
Comme dans les éditions précédentes de l'ICPP, la production du classement fait appel à deux approches méthodologiques différentes : une approche administrative, ou technique, une méthodologie pragmatique reflétant les connaissances et le jugement des experts ; et une approche statistique, utilisant l'analyse factorielle (AF), ou plus précisément la factorisation matricielle. L'utilisation de ces deux approches vise à garantir que le classement des performances des ports à conteneurs reflète le plus fidèlement possible les performances réelles des ports, tout en étant statistiquement robuste.
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Next is the Nihon Language Academy in East Delhi, renowned for its comprehensive curriculum and interactive teaching methods. They boast a faculty of experienced educators with a blend of both Indian and Japanese nationals. The academy provides extensive support for JLPT exam preparation along with personalized tutoring sessions if needed. Nihon Language Academy also arranges exchange programs with partner institutes in Japan, which provides students an opportunity to experience Japanese culture and language first-hand.
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CDO Webinar: Metadata and the CDO
- 1. Meta Data and the CDO © 2015 IMCue Solutions, Inc.
- 2. Background & Agenda 2 • Metadata Types and Categories • Trends in Metadata Technology • The CDO’s role in the Metadata Function
- 3. Definition of meta data – perspective • Cocktail party definition – “Data about data” • Business definition – Item Master for Data • Techno definition – Whatever we need to make it work • Usage-based definition – How you need to use it
- 4. Sample definition • Gartner – Data describing various facets of a data asset, for the purpose of improving its usability throughout its life cycle – Metadata unlocks the value of data, and therefore requires management attention [Gartner 2010] • IMCue – Data required to manage and use information assets successfully – The “DNA” of an enterprise 4
- 5. Meta Data to Date • Perceptions – Needed (maybe) – Sunk cost • Recent justification from regulations and NSA • Most organizations more serious – Sustainable meta data – Key component of information asset management 5
- 6. Metadata Types and Categories 6
- 8. DNA to Gartner xref Run Grow Transform reduce risks, eliminate inefficiency and improve responsiveness target improvements across the entire value chain attain new horizons, new markets and new models Define Trust Compliance Consistency Accuracy Recognition Understanding Navigate Compliance Quality Expedience Where used Leverage Location Collaboration Architecture Integrity Configuration Alignment Efficiency Scalability 8 Note: Business and Technical meta data have NOT been mentioned. This categorization is based on audience, and is not suitable for oversight
- 9. The CDO’s role in the Metadata Function 9
- 10. CDO’s Role • Plan – Match business needs with meta data features – Engage with stakeholders and benefactors – Not selling, but engaging for sustainability • Define – Focus on usable glossaries – Create sustainable processes – Define lineage aspects 10
- 11. DNA comes from Business Information Requirements 11 NEEDS BIRs DNA (Meta data requirements) Improve Customer Experience Objective Improve retention of households and next gen clients Business Action Prevent excessive delays in responding to client queries Information use (levers) Accurate understanding of accounts and holdings Business Information Requirements (BIRs) and Metrics House holding and family data quality Net promoter score Cross references household / business entities Data Candidates Client Household Demographics
- 12. CDO’s Role • Manage – Oversee use and value – Monitor cost – Ensure practical use – avoid dumpage • Operate – Verify Data Governance engaged with meta data – Verify use where desired • Sustain – Ensure adequate training and communications – Measure successes and value 12
- 13. Sample – Make models useful Seed • Acquire • Buy • Steal • Pattern Align & Identify Core Useful concept- ual Useful logical Physicals •Rationalize to technology Cross walk / Instant- iate Useful ?
- 14. Sample Case for Value Added Meta Data • Large health provider • The Challenge: – Over 350 inconsistent metrics – Slow and cumbersome to produce – Whose metrics should we trust? multiple departments create the same metrics… • The Solution: – Used 4 cross-functional groups to define and rationalize the metrics – Extracted definitional and behavior meta data manually • The Results: – Single version of 200 metrics – Seeded enterprise model – Enterprise level glossary of metrics and data elements 14
- 15. Trends in Metadata Technology 15
- 16. Trends • Pressure on traditional tools and new tools • Lineage • Registry / landscape • Data centric controls • Realistic approaches • New sources (Outlook) 16
- 17. Trends • Automatic collection • Big data / data lake management • Inventory management for the CDO • Intersection with ITIL • Moving away from relational • “Google” for data search 17
- 19. 19 Building Value Through Information Asset Management™ jladley@imcue.com 314-422-9076 19