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Data-Ed Online: Let's Talk Metadata: Strategies and Successes
 

Data-Ed Online: Let's Talk Metadata: Strategies and Successes

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This webinar originally aired on Tuesday, September 11, 2012. It is part of Data Blueprint's ongoing webinar series on data management with Dr. Aiken. ...

This webinar originally aired on Tuesday, September 11, 2012. It is part of Data Blueprint's ongoing webinar series on data management with Dr. Aiken.

Sign up for future sessions at http://www.datablueprint.com/webinar-schedule.

Abstract:
Commonly described as metadata management, properly implemented metadata practices incorporate data structures into more abstract processing. By using data about the data to enhance its value, its understandability, ease of use and many other options, organizations have developed sophisticated ways to enhance their data management and especially their data quality engineering efforts. Join us to learn more about specific metadata benefits and how to leverage it to achieve success within your organization.

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  • From Data Model Patterns: A Metadata Map By the way (yes, I know this is a losing battle, but I have to speak up…) data are plural. One of them is a datum.
  • Need distinction at least between “Business metadata” and “technical metadata”. Business people need descriptions of what is there and (in their terms) where to find it. A significant part of this is “provenance”—where did they come from? Technicians need database structures, search paths, etc. These are two very different things.
  • CSM? (Actually, CWM is a failure. Unfortunately, IMM is not going well. A combination of all of us getting tired and a couple of fundamental errors of premises.)
  • I am skeptical that there are any products supporting CWM. I ’d like to think that my book (2006) established the standards, but not enough people have read it. I believe that not enough people really understand what its structure should look like. Until they do, the thrashing will continue.
  • Correct answer: B
  • What you say here is (mostly) true. By the way, the premises that won ’t work in IMM are: All transformation between languages should go through a “core model” The problem is that there is 1) too much information loss, and 2) manual work for each translation (e.g., e/r to relational design.) The design models don ’t include a metamodel of the design components of UML. Their premise is that, since we are using UML to represent it, we don’t have to acknowledge it as a language for representing design. Meanwhile there is a lot of packaging going on.
  • I have no idea what this category is. In my book, I did distinguish across the 6 dimensions of the Zachman Framework, but in each column, I went from business owners through designers. Still distinguishing between business and technical metadata. In row two you have functions and business processes (current physical DFD). In row three you have “essential” data flow diagrams, without mechanisms and organized by events. In row three, you have programs. Data stores are “views” in the data column. Process dependencies are in the “where” column. Government and regulatory bodies are in the people and organizations column, and business rules are in the motivation column.
  • The definition of business metadata is: Data required for a businessperson to understand what is available and how to get it.
  • Ok, this is a major problem I have with the DMBOK. I go back to the original ANSI Standard. External schema is the view that any one worker has of the data. This is particular, concrete, and in terms of his language. This is John Z ’s row two and here things like OWL, SBVR and other attempts to capture language live. To me this is one half of the conceptual model. It may also be described in terms of entities, attributes, and relationships. The conceptual schema is the integrated view that encompasses all of the external schemas. I actually like to call it the architectural model, because I have renamed row three of the Zachman Fmwk the “architect’s view”. But this is the second half of the conceptual schema. This is in terms of entities, attributes, and relationships. The third ANSI schema they call the “internal schema”. This is the one that describes how data are actually stored on the computer. I believe that this is of two flavors: The Logical model describes the world in terms of a particular data management technology. This can be relational tables and columns, object oriented classes, or XML tags. (In 1975, the issue was network or hierarchy). This is not physical. The physical “model” is how the data are actually arranged on physical computers. This is about tablespaces, partitions, CPUs, etc. I believe that the DMBOK completely screwed this up, and I welcome the opportunity to contribute again. (My first contribution was completely ignored, by the way…)
  • For each model topic: - Blue outputs describe models - Reference to profile is to collections of “stereotypes” in UML to allow model to be represented in UML. (It took me a VERY long time to understand what was going on here. After all, the point of the different models is that they look different! It ’s going to be a while before this is ready for public consumption. (One of the problems is that we haven ’t had any vendors participating. Nobody owns it.)

Data-Ed Online: Let's Talk Metadata: Strategies and Successes Data-Ed Online: Let's Talk Metadata: Strategies and Successes Presentation Transcript

  • TITLE Welcome! Let’s Talk Metadata: Strategies and Successes Date: September 11, 2012 Time: 2:00 PM ET Presented by: Dr. Peter Aiken PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 8/14/2012 109/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Commonly Asked Questions 1) Will I get copies of the slides after the event? YES* 2) Is this being recorded so I can view it afterwards? YES* PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 8/14/2012 209/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Get Social With Us! Live Twitter Feed Like Us on Facebook Join the Group Join the conversation! www.facebook.com/datablueprintData Management & Follow us: Business Intelligence @datablueprint Post questions and Ask questions, gain @paiken comments insights and collaborate Find industry news, with fellow data Ask questions and submit insightful content management your comments: #dataed professionals and event updates. PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 8/14/2012 309/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Meet Your Presenter: Dr. Peter Aiken • Internationally recognized thought-leader in the data management field with more than 30 years of experience • Recipient of the 2010 International Stevens Award • Founding Director of Data Blueprint (http://datablueprint.com) • Associate Professor of Information Systems at Virginia Commonwealth University (http://vcu.edu) • President of DAMA International (http://dama.org) • DoD Computer Scientist, Reverse Engineering Program Manager/ Office of the Chief Information Officer • Visiting Scientist, Software Engineering Institute/Carnegie Mellon University • 7 books and dozens of articles • Experienced w/ 500+ data management practices in 20 countries #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 8/14/2012 409/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • Let’s Talk Metadata: Strategies and Successes Let’s Talk Metadata: Strategies and SuccessesDATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA23060 EDUCATION
  • TITLE Abstract: Metadata Practices This presentation describes how data management can be enhanced using meta- processing. Commonly described as metadata management, properly implemented metadata practices incorporate data structures into more abstract processing. By using data about the data to enhance its value, its understandability, its ease of use, and many other options – organizations have developed sophisticated ways to enhance their data management and especially their data quality engineering efforts. PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 609/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Outline 1. Data Management Overview 2. What is metadata and why is it important? 3. Types of metadata 4. Metadata for unstructured data 5. Strategy and implementation 6. Guiding Principles 7. Take Aways, References and Q&A Tweeting now: #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 8/14/2012 709/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE The DAMA Guide to the Data Management Body of Knowledge Published by DAMA International •The professional association for Data Managers (40 chapters worldwide) DMBoK organized around •Primary data management functions focused around data delivery to the organization •Organized around several environmental elements Data Management Functions PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 809/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE The DAMA Guide to the Data Management Body of Knowledge Amazon: http://www.amazon.com Or enter the terms "dama dm bok" at the Amazon search engine Environmental Elements PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 909/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Data Management PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 1009/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Data Management Manage data coherently. Manage data coherently. Data Program Coordination Share data across boundaries. Share data across boundaries. Organizational Assign responsibilities for data. Assign responsibilities for data. Data Integration Engineer data delivery systems. Engineer data delivery systems. Data Data Stewardship Development Data Support Maintain data availability. Maintain data availability. Operations PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 1109/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Data Management PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 1209/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International TITLE Metadata Management PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 131/26/201009/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Outline 1. Data Management Overview 2. What is metadata and why is it important? 3. Types of metadata 4. Metadata for unstructured data 5. Strategy and implementation 6. Guiding Principles 7. Take Aways, References and Q&A Tweeting now: #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 8/14/2012 1409/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Metadata or metadata • In the history of language, whenever two words are pasted together to form a combined concept initially, a hyphen links them. • With the passage of time, the hyphen is lost. The argument can be made that that time has passed. • There is a copyright on the term "metadata," but it has not been enforced. • So, term is "metadata" PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 1509/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Definitions Metadata is … •… everywhere in every data management activity and integral to all IT systems and applications. •… to data what data is to real life. Data reflects real life transactions, events, objects, relationships, etc. Metadata reflects data transactions, events, objects, relations, etc. •… the data that describe the structure and workings of an organization’s use of information, and which describe the systems it uses to manage that information. [quote from David Hays new book, page 4] •Data describing various facets of a data asset, for the purpose of improving its usability throughout its life cycle [Gartner 2010] •Metadata unlocks the value of data, and therefore requires management attention [Gartner 2010] Metadata Management is … •… the set of processes that ensure proper creation, storage, integration, and control to support associated use of metadata from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 1609/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Analogy: Card catalog in a library • Card catalog identifies what books are stored in the library and where they are located in the building • Users can search for books by subject area, author, or title • Catalog shows author, subject tags, publication date and revision history of each book • Card catalog information helps determine which books will meet the reader’s needs • Without this catalog resource, finding books in the library would be difficult, time consuming and frustrating • Readers may search many incorrect books before finding the right book if a catalog does not exist from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 1709/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • Definition, cont’d TITLE • Metadata is the card catalog in a managed data environment • Abstractly, Metadata is the descriptive tags or context on the data (the content) in a managed data environment • Metadata shows business and technical users where to find information in data repositories • Metadata provides details on where the data came from, how it got there, any transformations, and its level of quality • Metadata provides assistance with what the data really means and how to interpret it from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 1809/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Defining Metadata Who Metadata is any What How combination of any circle and the Data data in the center of the spark! Where Why When Adapted from Brad Melton PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 1909/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • Library Metadata Example TITLE Libraries can operate efficiently through careful use of metadata (Card Catalog) Who: Author What: Title Who Where: Shelf Location What How When: Publication Dat Dat Date Data Data a a Library Book Manage a large amount of data (the Why Where Library) with a small amount of metadata When (Card Catalog) PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 2009/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Outlook Example Who "Outlook" metadata is used to navigate and manage email What How Imagine how Data Messages managing e-mail (already non-trivial) would change if Where Why Outlook did not make use of metadata When PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 2109/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Outlook Example, cont’d Who: "To" & "From" What: "Subject" How: "Priority" Where:"USERID/Inbox", "USERID/Personal Folders" Why: "Body" When: "Sent" & "Received” •Find the important stuff/weed out junk •Organize for future access/outlook rules PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 2209/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • Metadata practices connect data sources and TITLE uses in an organized and efficient manner Metadata Practices Metadata Metadata Metadata Engineering Storage Delivery Sources Uses Metadata Governance • What is the structure of metadata practices? – Storage: repository, glossary, models, lineage - currently multiple technologies are used – Engineering: identifying/harvesting/normalizing/administer evolving metadata structures – Delivery: supply/access/portal/definition/lookup search identify/ensure required metadata supplies to meet business needs – Governance: ensure proper/creation/storage/integration/control to support effective use • When executed, engineering and delivery implement governance PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 2309/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • Metadata Practices will be inextricably intertwined with TITLE Extraction Data Quality and Master Data and Knowledge Sources Management, (among other EIM Functions) Organized Knowledge Data Knowledge Management Practices Routine Data Scans Data Organization Practices Data that might benefit from Suspected/ Master Management Identified Master Data Catalogs Data Quality Master Data Problems Management Data Quality Practices EngineeringRoutine Data Scans Improved Quality Data Operational Data PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 2409/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Metadata History 1990-2008 The history of Metadata management tools and products seems to be a metaphor for the lack of a methodological approach to enterprise information management: • Lack of standards and proprietary nature of most managed Metadata solutions cause many organizations to avoid focusing on metadata • This limits organizations’ ability to develop a true enterprise information management environment • Increased attention given to information and its importance to an organization’s operations and decision-making will drive Metadata management products and solutions to become more standardized • More recognition to the need for a methodological approach to managing information and metadata PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 2509/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Metadata History: The 1990s • Business managers began to recognize the value of Metadata repositories • Newer tools expanded the scope • Potential benefits identified during this period include: – Providing semantic layer between company’s system and business users – Reducing training costs – Making strategic information more valuable as aid in decision making – Creating actionable information – Limiting incorrect decisions PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 2609/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Metadata History: Mid-to late 1990s • Metadata becomes more relevant to corporations who were struggling to understand their information resources caused by: – Y2K deadline – Emerging data warehousing initiatives – Growing focus around the World Wide Web • Beginning of efforts to try to standardize Metadata definition and exchange between applications in the enterprise • Examples of standardization: – 1995: CASE Definition Interchange Facility (CDIF) – 1995: Dublin Core Metadata Elements – 1994 – 1999: First parts of ISO 11179 standard for Specification and Standardization of Data Elements were published – 1998: Common Warehouse Metadata Model (CWM) – 1995: Metadata Coalitions’ (MDC) Open Information Model – 2000: Both standards merged into CSM. Many Metadata repositories began promising adoption of CWM standard PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 2709/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Metadata History: 21st Century • Update of existing Metadata repositories for deployment on the web • Introduction of products to support CWM • Vendors begin focusing on Metadata as an additional product offering • Few organizations purchase or develop Metadata repositories • Effective enterprise-wide Managed Metadata Environments are rare due to: – Scarcity of people with real world skills – Difficulty of the effort – Less than stellar success of some of the initial efforts at some companies – Stagnation of the tool market after the initial burst of interest in late 90s – Still less than universal understanding of the business benefits – Too heavy emphasis on legacy applications and technical metadata PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 2809/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Polling Question #1 What have been the driving factors in focusing on metadata within the last decade? a. Recent entry of smaller vendors into the market b. Challenges related to addressing regulatory requirements c. Declination to the existing Metadata standards PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 7/10/2012 2909/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Metadata History: Current Decade • Focus on need for and importance of metadata • Focus on how to incorporate Metadata beyond traditional structured sources and include unstructured sources • Driving factors: – Recent entry of larger vendors into the market – Challenges related to addressing regulatory requirements, e.g. Sarbanes-Oxley, and privacy requirements with unsophisticated tools – Emergence of enterprise-wide initiatives, e.g. information governance, compliance, enterprise architecture, automated software reuse – Improvements to the existing Metadata standards, e.g. RFP release of new OMG standard Information Management Metamodel (IMM), which will replace CWM – Recognition at the highest levels that information is an asset that must be actively and effectively managed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 3009/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Outline 1. Data Management Overview 2. What is metadata and why is it important? 3. Types of metadata 4. Metadata for unstructured data 5. Strategy and implementation 6. Guiding Principles 7. Take Aways, References and Q&A Tweeting now: #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 8/14/2012 3109/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Types of Metadata: Process Metadata • Process Metadata is... – Data that defines and describes the characteristics of other system elements, e.g. processes, business rules, programs, jobs, tools, etc. • Examples of Process metadata: – Data stores and data involved – Government/regulatory bodies – Organization owners and stakeholders – Process dependencies and decomposition – Process feedback loop and documentation – Process name from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 3209/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Business Process Metadata Who Who: Created the document What How ation? What: Are the Data important dependen cies Why Where among the processes When ? PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W.Do the How: BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 3309/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Types of Metadata: Business Metadata • Business Metadata describe to the end user what data are available, what they mean and how to retrieve them. • Included are: – Business names and definitions of subject and concept areas, entities, attributes – Attribute data types and other attribute properties – Range descriptions, calculations, algorithms and business rules – Valid domain values and their definitions from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 3409/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Types of Metadata: Technical & Operational Metadata • Technical and operational metadata provides developers and technical users with information about their systems • Technical metadata includes… – Physical database table and column names, column properties, other properties, other database object properties and database storage • Operational metadata is targeted at IT operations users’ needs, including… – Information about data movement, source and target systems, batch programs, job frequency, schedule anomalies, recovery and backup information, archive rules and usage • Examples of Technical & Operational metadata: – Audit controls and balancing information – Data archiving and retention rules – Encoding/reference table conversions – History of extracts and results from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 3509/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Types of Metadata: Data Stewardship • Data stewardship Metadata is about... – Data stewards, stewardship processes, and responsibility assignments • Data stewards… – Assure that data and Metadata are accurate, with high quality across the enterprise. – Establish and monitor data sharing. • Examples of Data stewardship metadata: – Business drivers/goals – Data CRUD rules – Data definitions – business and technical – Data owners – Data sharing rules and agreements/contracts – Data stewards, roles and responsibilities from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 3609/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Types of Metadata: Provenance • Provenance: – the history of ownership of a valued object or work of art or literature" [Merriam Webster] – For each datum, this is the description of: • Its source (system or person or department), • Any derivation used, and • The date it was created. – Examples of Data Provenance: • The programs or processes by which it was created • Its owner • The steward responsible for its quality • Other roles and responsibilities • Rules for sharing it. from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 3709/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Outline 1. Data Management Overview 2. What is metadata and why is it important? 3. Types of metadata 4. Metadata for unstructured data 5. Strategy and implementation 6. Guiding Principles 7. Take Aways, References and Q&A Tweeting now: #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 8/14/2012 3809/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Metadata Subject Areas Subject Areas Components 1) Business Analytics Data definitions, reports, users, usage, performance 2) Business Architecture Roles and organizations, goals and objectives Business terms and explanations for a particular 3) Business Definitions concept, fact, or other item found in an organization 4) Business Rules Standard calculations and derivation methods Policies, standards, procedures, programs, roles, 5) Data Governance organizations, stewardship assignments Sources, targets, transformations, lineage, ETL 6) Data Integration workflows, EAI, EII, migration/conversion 7) Data Quality Defects, metrics, ratings Unstructured data, documents, taxonomies, 8) Document Content ontologies, name sets, legal discovery, search engine Management indexes from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 3909/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Metadata Subject Areas, cont’d Subject Areas Components 9) Information Technology Platforms, networks, configurations, licenses Infrastructure Entities, attributes, relationships and rules, business 10) Conceptual data models names and definitions. Files, tables, columns, views, business definitions, 11) Logical Data Models indexes, usage, performance, change management Functions, activities, roles, inputs/outputs, workflow, 12) Process Models timing, stores 13) Systems Portfolio and IT Databases, applications, projects, and programs, Governance integration roadmap, change management 14) Service-oriented Architecture (SOA) Components, services, messages, master data information: 15) System Design and Requirements, designs and test plans, impact Development Data security, licenses, configuration, reliability, 16) Systems Management service levels from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 4009/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Benefits of Metadata 1) Increase the value of strategic information (e.g. data warehousing, CRM, SCM, etc.) by providing context for the data, thus aiding analysts in making more effective decisions. 2) Reduce training costs and lower the impact of staff turnover through thorough documentation of data context, history, and origin. 3) Reduce data-oriented research time by assisting business analysts in finding the information they need in a timely manner. 4) Improve communication by bridging the gap between business users and IT professionals, leveraging work done by other teams and increasing confidence in IT system data. 5) Increased speed of system development’s time-to-market by reducing system development life-cycle time. 6) Reduce risk of project failure through better impact analysis at various levels during change management. 7) Identify and reduce redundant data and processes, thereby reducing rework and use of redundant, out-of-data, or incorrect data. from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 411/26/201009/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Metadata for Unstructured Data • Unstructured data = any data that is not in a database or data file, including documents or other media data • Metadata describes both structured and unstructured data • Metadata for unstructured data exists in many formats, responding to a variety of different requirements • Examples of Metadata repositories describing unstructured data: – Content management applications – University websites – Company intranet sites – Data archives – Electronic journals collections – Community resource lists • Common method for classifying Metadata in unstructured sources is to describe them as descriptive metadata, structural metadata, or administrative metadata from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 421/26/201009/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Metadata for Unstructured Data: Examples Examples of descriptive metadata: • Catalog information • Thesauri keyword terms Examples of administrative metadata • Source(s) Examples of structural • Integration/update schedule • Access rights metadata • Page relationships (e.g. site • Dublin Core navigational design) • Field structures • Format (audio/visual, booklet) • Thesauri keyword labels • XML schemas PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 4309/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Sources of Metadata Primary Sources: • Virtually anything named in an organization Secondary sources: • Other Metadata repositories, accessed using bridge software • CASE tools, ETL tools Many data management tools create and use repositories for their own use. PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 4409/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • } TITLE Specific Example Four metadata sources: ADRM 1.Existing reference models (i.e., ADRM) 2.Conceptual model created two years ago 3.Existing systems (to be reverse engineered) 4.Enterprise data model PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 4509/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Outline 1. Data Management Overview 2. What is metadata and why is it important? 3. Types of metadata 4. Metadata for unstructured data 5. Strategy and implementation 6. Guiding Principles 7. Take Aways, References and Q&A Tweeting now: #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 8/14/2012 4609/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Metadata Strategy • Metadata Strategy is… – … a statement of direction in Metadata management by the enterprise – … a statement of intend that acts as a reference framework for the development teams – …driven by business objectives and prioritized by the business value they bring to the organization • Build a Metadata strategy from a set of defined components • Primary focus of Metadata strategy: gain an understanding of and consensus on the organization’s key business drivers, issues, and information requirements for the enterprise Metadata program • Need to understand how well the current environment meets these requirements now and in the future • Metadata strategy objectives define the organization’s future enterprise Metadata architecture and recommend logical progression of phased implementation steps PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 4709/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Metadata Strategy Implementation Phases PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 4809/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Metadata Management                                                         PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 491/26/201009/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Goals and Principles 1. Provide organizational understanding of terms and usage 2. Integrate Metadata from diverse sources 3. Provide easy, integrated access to metadata 4. Ensure Metadata quality and security from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 501/26/201009/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Activities 1) Understand Metadata requirements 2) Define the Metadata architecture 3) Develop and maintain Metadata standards 4) Implement a managed Metadata environment 5) Create and maintain metadata 6) Integrate metadata 7) Management Metadata repositories 8) Distribute and deliver metadata 9) Query, report and analyze metadata from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 511/26/201009/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Activities: Metadata Standards Types • Two major types exist: 1) Industry or consensus standards 2) International standards • High level framework shows how standards are related and how they rely on each other for context and usage: from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 5209/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Activities: Noteworthy Metadata Standards Types Common Warehouse Metadata (CWM): • Specifies the interchange of Metadata among data warehousing, BI, KM, and portal technologies. • Based on UML and depends on it to represent object-oriented data constructs. The CWM Metamodel Management Warehouse Process Warehouse Operation Data Information Business Analysis Transformation OLAP Mining Visualization Nomenclature Object Resource Relational Record Multidimensional XML Model Business Keys and Type Software Data Types Expression Foundation Information Indexes Mapping Deployment Object Model PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 5309/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Information Management Metamodel (IMM) • Object Management Group Project to replace CWM • Concerned with: – Business Modeling • Entity/relationship metamodel – Technology modeling • Relational Databases • XML • LDAP – Model Management • Traceability – Compatibility with related models • Semantics of business vocabulary and business rules • Ontology Definition Metamodel PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 5409/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE The Information Management Metamodel... • Based on Core model. • Used to translate from one model to another. PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 5509/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Primary Deliverables • Metadata repositories • Quality metadata • Metadata analysis • Data lineage • Change impact analysis • Metadata control procedures • Metadata models and architecture • Metadata management operational analysis from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 561/26/201009/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Roles and Responsibilities Suppliers: – Data Stewards – Data Architects – Data Modelers – Database Administrators – Other Data Professionals – Data Brokers – Government and Industry Regulators Participants: – Metadata Specialists – Data Integration Architects Consumers: – Data Stewards – Data Architects and Modelers • Data Stewards – Database Administrators • Data Professionals – Other DM Professionals • Other IT Professionals – Other IT Professionals • Knowledge Workers – DM Executives • Managers and Executives – Business Users • Customers and Collaborators • Business Users from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 571/26/201009/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Technology • Metadata repositories • Data modeling tools • Database management systems • Data integration tools • Business intelligence tools • System management tools • Object modeling tools • Process modeling tools • Report generating tools • Data quality tools • Data development and administration tools • Reference and mater data management tools from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 5809/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Outline 1. Data Management Overview 2. What is metadata and why is it important? 3. Types of metadata 4. Metadata for unstructured data 5. Strategy and implementation 6. Guiding Principles 7. Take Aways, References and Q&A Tweeting now: #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 8/14/2012 5909/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Guiding Principles 1) Establish and maintain a Metadata strategy and appropriate policies, especially clear goals and objectives for Metadata management and usage 2) Secure sustained commitment, funding, and vocal support from senior management concerning Metadata management for the enterprise 3) Take an enterprise perspective to ensure future extensibility, but implement through iterative and incremental delivery 4) Develop a Metadata strategy before evaluating, purchasing, and installing Metadata management products 5) Create or adopt Metadata standards to ensure interoperability of Metadata across the enterprise 6) Ensure effective Metadata acquisition for internal and external metadata 7) Maximize user access since a solution that is not accessed or is under-accessed will not show business value from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 6009/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Guiding Principles, cont’d 8) Understand and communicate the necessity of Metadata and the purpose of each type of metadata; socialization of the value of Metadata will encourage business usage 9) Measure content and usage 10) Leverage XML, messaging and web services 8) Establish and maintain enterprise-wide business involvement in data stewardship, assigning accountability for metadata 9) Define and monitor procedures and processes to ensure correct policy implementation 10) Include a focus on roles, staffing, standards, procedures, training, and metrics 11) Provide dedicated Metadata experts to the project and beyond 12) Certify Metadata quality from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 6109/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Using metadata descriptions of Bluetooth devices Data Column Attributes/Fields CGL Trackpad Keyboard VCU IDR Trackpad Motorola S9 Motorola S9 Peters i4 Peters i4 Trackpad CGL VCU Keyboard Trackpad IDR VCU Trackpad Trackpad VCU PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 6209/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Example: iTunes Metadata • Example: – iTunes Metadata • Insert a recently purchased CD • iTunes can: – Count the number of tracks (25) – Determine the length of each track PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 6309/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Example: iTunes Metadata • When connected to the Internet iTunes connects to the Gracenote(.com) Media Database and retrieves: – CD Name – Artist – Track Names – Genre – Artwork • Sure would be a pain to type in all this information PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 6409/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Example: iTunes Metadata • To organize iTunes – I create a "New Smart Playlist" for Artists containing "Miles Davis" PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 6509/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Example: iTunes Metadata • Notice I didnt get the desired results • I already had another Miles Davis recording in iTunes • Must fine-tune the request to get the desired results – Album contains "The complete birth of the cool" • Now I can move the playlist "Miles Davis" PRODUCED BY to a folder CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 6609/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Example: iTunes Metadata • The same: – Interface – Processing – Data Structures • are applied to – Podcasts – Movies – Books – .pdf files • Economies of scale are enormous CLASSIFICATION DATE SLIDE PRODUCED BY DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 6709/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Outline 1. Data Management Overview 2. What is metadata and why is it important? 3. Types of metadata 4. Metadata for unstructured data 5. Strategy and implementation 6. Guiding Principles 7. Take Aways, References and Q&A Tweeting now: #dataed PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 8/14/2012 6809/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Summary from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 691/26/201009/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE References & Recommended Reading from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 701/26/201009/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE References, cont’d from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 711/26/201009/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE References, cont’d from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 721/26/201009/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE References, cont’d from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 09/14/12 731/26/201009/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Questions? + = It’s your turn! Use the chat feature or Twitter (#dataed) to submit your questions to Peter now. PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 8/14/2012 7409/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!
  • TITLE Upcoming Events October Webinar: Engineering Solutions to Data Quality Challenges October 9, 2012 @ 2:00 PM – 3:30 PM ET (11:00 AM-12:30 PM PT) November Webinar: Get the Most Out of Your Tools: Data Management Technologies November 13, 2012 @ 2:00 PM – 3:30 PM ET (11:00 AM-12:30 PM PT) Sign up here: •www.datablueprint.com/webinar-schedule •www.Dataversity.net Brought to you by: PRODUCED BY CLASSIFICATION DATE SLIDE DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION 8/14/2012 7509/14/12 © Copyright this and previous years by Data Blueprint - all rights reserved!