Certain systems are more data focused than others. Usually their primary focus is on accomplishing integration of disparate data. In these cases, failure is most often attributable to the adoption of a single pillar (silver bullet). The three webinars in the Data Systems Integration and Business Value series are designed to illustrate that good systems development more often depends on at least three DM disciplines (pie wedges) in order to provide a solid foundation.
Much of the discussion of metadata focuses on understanding it and the associated technologies. While these are important, they represent a typical tool/technology focus and this has not achieved significant results to date. A more relevant question when considering pockets of metadata is: Whether to include them in the scope organizational metadata practices. By understanding what it means to include items in the scope of your metadata practices, you can begin to build systems that allow you to practice sophisticated ways to advance their data management and supported business initiatives. After a bit of practice in this manner you can position your organization to better exploit any and all metadata technologies.
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Data Systems Integration & Business Value Pt. 1: Metadata
1. Copyright 2013 by Data Blueprint
Data Systems Integration & Business Value Part 1: Metadata
Certain systems are more data focused than others. Usually their
primary focus is on accomplishing integration of disparate data. In
these cases, failure is most often attributable to the adoption of a
single pillar (silver bullet). The three webinars in the Data Systems
Integration and Business Value series are designed to illustrate that
good systems development more often depends on at least three
DM disciplines (pie wedges) in order to provide a solid foundation.
Much of the discussion of metadata focuses on understanding it and
the associated technologies. While these are important, they
represent a typical tool/technology focus and this has not achieved
significant results to date. A more relevant question when
considering pockets of metadata is: Whether to include them in the
scope organizational metadata practices. By understanding what it
means to include items in the scope of your metadata practices, you
can begin to build systems that allow you to practice sophisticated
ways to advance their data management and supported
business initiatives. After a bit of practice in this manner
you can position your organization to better exploit any
and all metadata technologies.
Date: July 9, 2013
Time: 2:00 PM ET/11:00 AM PT
Presenter: Peter Aiken, Ph.D.
1
2. Copyright 2013 by Data Blueprint
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3. Copyright 2013 by Data Blueprint
3
Peter Aiken, PhD
• 25+ years of experience in data
management
• Multiple international awards &
recognition
• Founder, Data Blueprint (datablueprint.com)
• Associate Professor of IS, VCU (vcu.edu)
• President, DAMA International (dama.org)
• 8 books and dozens of articles
• Experienced w/ 500+ data
management practices in 20 countries
• Multi-year immersions with
organizations as diverse as the
US DoD, Nokia, Deutsche Bank,
Wells Fargo, and the Commonwealth
of Virginia
4. Data Systems Integration & Business
Value Part 1: Metadata
Presented by Peter Aiken, Ph.D.
10124 W. Broad Street, Suite C
Glen Allen, Virginia 23060
804.521.4056
5. Copyright 2013 by Data Blueprint
1. Data Management Overview
2. What is metadata and why is it important?
3. Major metadata types & subject areas
4. Metadata benefits, application & sources
5. Metadata strategies & implementation
6. Metadata building blocks
7. Guiding Principles
8. Specific teachable example
9. Take Aways, References and Q&A Tweeting now:
#dataed
Outline
1. Data Management Overview
2. What is metadata and why is it important?
3. Major metadata types & subject areas
4. Metadata benefits, application & sources
5. Metadata strategies & implementation
6. Metadata building blocks
7. Guiding Principles
8. Specific teachable example
9. Take Aways, References and Q&A
5
6. Copyright 2013 by Data Blueprint
1. Data Management Overview
2. What is metadata and why is it important?
3. Major metadata types & subject areas
4. Metadata benefits, application & sources
5. Metadata strategies & implementation
6. Metadata building blocks
7. Guiding Principles
8. Specific teachable example
9. Take Aways, References and Q&A Tweeting now:
#dataed
Outline
6
7. Data Program
Coordination
Feedback
Data
Development
Copyright 2013 by Data Blueprint
Standard
Data
Five Integrated DM Practice Areas
Organizational Strategies
Goals
Business
Data
Business Value
Application
Models &
Designs
Implementation
Direction
Guidance
7
Organizational
Data Integration
Data
Stewardship
Data Support
Operations
Data
Asset Use
Integrated
Models
Leverage data in organizational activities
Data management
processes and
infrastructure
Combining multiple
assets to produce
extra value
Organizational-entity
subject area data
integration
Provide reliable data
access
Achieve sharing of data within a
business area
8. Copyright 2013 by Data Blueprint
Five Integrated DM Practice Areas
Manage data coherently.
Share data across boundaries.
Assign responsibilities for data.
Engineer data delivery systems.
Maintain data availability.
Data Program
Coordination
Organizational Data
Integration
Data Stewardship Data Development
Data Support
Operations
8
9. • 5 Data management
practices areas / data
management
basics ...
• ... are necessary but
insufficient
prerequisites to
organizational data
leveraging
applications that is
self actualizing data or
advanced data
practices
Copyright 2013 by Data Blueprint
Hierarchy of Data Management Practices (after Maslow)
Basic Data Management Practices
– Data Program Management
– Organizational Data Integration
– Data Stewardship
– Data Development
– Data Support Operations
http://3.bp.blogspot.com/-ptl-9mAieuQ/T-idBt1YFmI/AAAAAAAABgw/Ib-nVkMmMEQ/s1600/maslows_hierarchy_of_needs.png
Advanced
Data
Practices
• Cloud
• MDM
• Mining
• Big Data
• Analytics
• Warehousing
• SOA
9
10. Copyright 2013 by Data Blueprint
Data Management
Body of
Knowledge
10
Data
Management
Functions
11. • Data Management Body of Knowledge
(DMBOK)
– Published by DAMA International, the
professional association for
Data Managers (40 chapters worldwide)
– Organized around primary data management
functions focused around data delivery to the
organization and several environmental
elements
• Certified Data Management
Professional (CDMP)
– Series of 3 exams by DAMA International and
ICCP
– Membership in a distinct group of
fellow professionals
– Recognition for specialized knowledge in a
choice of 17 specialty areas
– For more information, please visit:
• www.dama.org, www.iccp.org
Copyright 2013 by Data Blueprint
DAMA DM BoK & CDMP
11
13. Copyright 2013 by Data Blueprint
1. Data Management Overview
2. What is metadata and why is it important?
3. Major metadata types & subject areas
4. Metadata benefits, application & sources
5. Metadata strategies & implementation
6. Metadata building blocks
7. Guiding Principles
8. Specific teachable example
9. Take Aways, References and Q&A Tweeting now:
#dataed
Outline
13
14. Copyright 2013 by Data Blueprint
1. Data Management Overview
2. What is metadata and why is it important?
3. Major metadata types & subject areas
4. Metadata benefits, application & sources
5. Metadata strategies & implementation
6. Metadata building blocks
7. Guiding Principles
8. Specific teachable example
9. Take Aways, References and Q&A Tweeting now:
#dataed
Outline
14
15. Copyright 2013 by Data Blueprint
Meta-data 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"
15
16. Copyright 2013 by Data Blueprint
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 Hay's 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 2011]
• Metadata Management is
– The set of processes that ensure proper creation, storage, integration, and
control to support associated use of metadata
16
19. Copyright 2013 by Data Blueprint
Defining Metadata
Metadata is any
combination of any
circle and the data
in the center that
unlocks the value
of the data!
Adapted
from
Brad
Melton
Data
WhereWhy
What How
Who
When
Data
19
20. Copyright 2013 by Data Blueprint
Who: Author
What: Title
Where: Shelf
Location
When: Publication
Date
A small amount of
metadata (Card
Catalog) unlocks the
value of a large amount
of data (the Library)
Library Metadata Example
Libraries can operate efficiently through careful
use of metadata (Card Catalog)
20
Data
WhereWhy
What How
Who
When
Library
Book
21. Copyright 2013 by Data Blueprint
Outlook Example
"Outlook" metadata is
used to navigate and
manage email
Imagine how
managing e-mail
(already non-trivial)
would change if
Outlook did not make
use of metadata
21
Data
WhereWhy
What How
Who
When
Email
Message
22. Copyright 2013 by Data Blueprint
Who: "To" & "From"
What: "Subject"
How: "Priority"
Where: "USERID/Inbox",
"USERID/Personal"
Why: "Body"
When: "Sent" & "Received”
• Find the important stuff/weed
out junk
• Organize for future access/
outlook rules
Outlook Example, continued
22
23. Uses
Copyright 2013 by Data Blueprint
What is the structure of metadata practices?
• Metadata practices connect data sources and uses in an
organized and efficient manner
– 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
Sources
Metadata Governance
Metadata
Engineering
Metadata
Delivery
Metadata Practices
Metadata
Storage
23
Specialized Team Skills
24. Extraction
Sources
Copyright 2013 by Data Blueprint
Organized Knowledge 'Data'
Improved
Quality
Data
Data Organization Practices
Metadata Practices will be inextricably intertwined with
Data Quality and Master Data and Knowledge
Management, (among other functions)
Opera<onal
Data
Data
Quality
Engineering
Master
Data
Management
Prac<ces
Suspected/
Iden<fied
Data
Quality
Problems
Routine Data Scans
Master Data Catalogs
Routine Data Scans
Knowledge
Management
Prac<ces
Data
that
might
benefit
from
Master
Management
24
25. Copyright 2013 by Data Blueprint
Polling Question #1
• My organization began using or is planning to use a formal
approach to metadata management
a) Last year (2012)
b) This year (2013)
c) Next year (2014)
d) Not at all
25
26. Copyright 2013 by Data Blueprint
1. Data Management Overview
2. What is metadata and why is it important?
3. Major metadata types & subject areas
4. Metadata benefits, application & sources
5. Metadata strategies & implementation
6. Metadata building blocks
7. Guiding Principles
8. Specific teachable example
9. Take Aways, References and Q&A Tweeting now:
#dataed
Outline
26
27. Copyright 2013 by Data Blueprint
1. Data Management Overview
2. What is metadata and why is it important?
3. Major metadata types & subject areas
4. Metadata benefits, application & sources
5. Metadata strategies & implementation
6. Metadata building blocks
7. Guiding Principles
8. Specific teachable example
9. Take Aways, References and Q&A Tweeting now:
#dataed
Outline
27
29. Copyright 2013 by Data Blueprint
Business Process Metadata
Who: Created the
documentation?
What: Are the important
dependencies
among the
processes?
How: Do the business
processes
interact with each
other?
29
Data
WhereWhy
What How
Who
When
Email
Message
36. Copyright 2013 by Data Blueprint
1. Data Management Overview
2. What is metadata and why is it important?
3. Major metadata types & subject areas
4. Metadata benefits, application & sources
5. Metadata strategies & implementation
6. Metadata building blocks
7. Guiding Principles
8. Specific teachable example
9. Take Aways, References and Q&A Tweeting now:
#dataed
Outline
36
37. Copyright 2013 by Data Blueprint
1. Data Management Overview
2. What is metadata and why is it important?
3. Major metadata types & subject areas
4. Metadata benefits, application & sources
5. Metadata strategies & implementation
6. Metadata building blocks
7. Guiding Principles
8. Specific teachable example
9. Take Aways, References and Q&A Tweeting now:
#dataed
Outline
37
40. Copyright 2013 by Data Blueprint
Metadata for Unstructured Data: Examples
• Examples of descriptive metadata:
– Catalog information
– Thesauri keyword terms
• Examples of structural metadata
– Dublin Core
– Field structures
– Format (audio/visual, booklet)
– Thesauri keyword labels
– XML schemas
• Examples of administrative metadata
– Source(s)
– Integration/update schedule
– Access rights
– Page relationships (e.g. site navigational design)
40
41. Copyright 2013 by Data Blueprint
Specific Example
• Four metadata sources:
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
} 41
42. Copyright 2013 by Data Blueprint
1. Data Management Overview
2. What is metadata and why is it important?
3. Major metadata types & subject areas
4. Metadata benefits, application & sources
5. Metadata strategies & implementation
6. Metadata building blocks
7. Guiding Principles
8. Specific teachable example
9. Take Aways, References and Q&A Tweeting now:
#dataed
Outline
42
43. Copyright 2013 by Data Blueprint
1. Data Management Overview
2. What is metadata and why is it important?
3. Major metadata types & subject areas
4. Metadata benefits, application & sources
5. Metadata strategies & implementation
6. Metadata building blocks
7. Guiding Principles
8. Specific teachable example
9. Take Aways, References and Q&A Tweeting now:
#dataed
Outline
43
44. Copyright 2013 by Data Blueprint
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
44
45. Copyright 2013 by Data Blueprint
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
45
46. Copyright 2013 by Data Blueprint
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
46
47. Copyright 2013 by Data Blueprint
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
47
48. Copyright 2013 by Data Blueprint
Metadata History: Current Decade
• Focus on need for and importance of metadata
• Focus on how to incorporate Metadata beyond traditional
structured sources and include semistructured 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
48
49. Copyright 2013 by Data Blueprint
Why Metadata Matters
• They know you rang a phone sex service at 2:24 am and spoke for 18
minutes. But they don't know what you talked about.
• They know you called the suicide prevention hotline from the Golden
Gate Bridge. But the topic of the call remains a secret.
• They know you spoke with an HIV testing service, then your doctor, then
your health insurance company in the same hour. But they don't know
what was discussed.
• They know you received a call from the local NRA office while it was
having a campaign against gun legislation, and then called your
senators and congressional representatives immediately after. But the
content of those calls remains safe from government intrusion.
• They know you called a gynecologist, spoke for a half hour, and then
called the local Planned Parenthood's number later that day. But nobody
knows what you spoke about.
– https://www.eff.org/deeplinks/2013/06/why-metadata-matters
49
50. Copyright 2013 by Data Blueprint
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
• Only 1 in 10 organizations has a documented, board approved data
strategy
50
51. Copyright 2013 by Data Blueprint
Polling Question #2
• Compliance laws have influenced my organization to pay
more attention to and/or put more resources into:
a) Data quality improvement efforts
b) Metadata management efforts
c) Database management, in general
d) No impact
51
52. Copyright 2013 by Data Blueprint
Metadata Strategy Implementation Phases
52
53. Copyright 2013 by Data Blueprint
1. Data Management Overview
2. What is metadata and why is it important?
3. Major metadata types & subject areas
4. Metadata benefits, application & sources
5. Metadata strategies & implementation
6. Metadata building blocks
7. Guiding Principles
8. Specific teachable example
9. Take Aways, References and Q&A Tweeting now:
#dataed
Outline
53
54. Copyright 2013 by Data Blueprint
1. Data Management Overview
2. What is metadata and why is it important?
3. Major metadata types & subject areas
4. Metadata benefits, application & sources
5. Metadata strategies & implementation
6. Metadata building blocks
7. Guiding Principles
8. Specific teachable example
9. Take Aways, References and Q&A Tweeting now:
#dataed
Outline
54
56. Copyright 2013 by Data Blueprint
Polling Question #3
• My organization began using or is planning to use a
metadata repository (purchased or homegrown)
a) Last year (2012)
b) This year (2013)
c) Next year (2014)
d) Not applicable
56
59. Copyright 2013 by Data Blueprint
• 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
Activities: Noteworthy Metadata Standards Types
Warehouse
ProcessWarehouse
ProcessWarehouse
Process Warehouse
Opera;onWarehouse
Opera;onWarehouse
Opera;on
Transforma<onTransforma<on OLAP
Data
Mining
Informa<on
Visualiza<on
Business
Nomenclature
Object
Model Rela<onal Record Mul<dimensionalMul<dimensional XML
Business
Informa<on
Data
Types Expression
Keys
and
Indexes
Type
Mapping
SoOware
Deployment
Object
ModelObject
ModelObject
ModelObject
ModelObject
ModelObject
Model
Management
Analysis
Resource
Founda<on
59
60. Copyright 2013 by Data Blueprint
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
• Based on Core model
• Used to translate from
one model to another
60
64. Copyright 2013 by Data Blueprint
Polling Question #4
• Do you use metadata models and/or modeling tools to
support your information quality efforts?
a) Yes
b) No
64
65. Copyright 2013 by Data Blueprint
1. Data Management Overview
2. What is metadata and why is it important?
3. Major metadata types & subject areas
4. Metadata benefits, application & sources
5. Metadata strategies & implementation
6. Metadata building blocks
7. Guiding Principles
8. Specific teachable example
9. Take Aways, References and Q&A Tweeting now:
#dataed
Outline
65
66. Copyright 2013 by Data Blueprint
1. Data Management Overview
2. What is metadata and why is it important?
3. Major metadata types & subject areas
4. Metadata benefits, application & sources
5. Metadata strategies & implementation
6. Metadata building blocks
7. Guiding Principles
8. Specific teachable example
9. Take Aways, References and Q&A Tweeting now:
#dataed
Outline
66
69. Copyright 2013 by Data Blueprint
1. Data Management Overview
2. What is metadata and why is it important?
3. Major metadata types & subject areas
4. Metadata benefits, application & sources
5. Metadata strategies & implementation
6. Metadata building blocks
7. Guiding Principles
8. Specific teachable example
9. Take Aways, References and Q&A Tweeting now:
#dataed
Outline
69
70. Copyright 2013 by Data Blueprint
1. Data Management Overview
2. What is metadata and why is it important?
3. Major metadata types & subject areas
4. Metadata benefits, application & sources
5. Metadata strategies & implementation
6. Metadata building blocks
7. Guiding Principles
8. Specific teachable example
9. Take Aways, References and Q&A Tweeting now:
#dataed
Outline
70
71. Copyright 2013 by Data Blueprint 6609/10/12
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
71
72. Copyright 2013 by Data Blueprint 6709/10/12
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
72
73. Copyright 2013 by Data Blueprint 6809/10/12
Example: iTunes Metadata
• To organize iTunes
– I create a "New Smart
Playlist" for Artist's
containing "Miles Davis"
73
74. Copyright 2013 by Data Blueprint
Example: iTunes Metadata
6909/10/12
• Notice I didn't
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" to a
folder
74
75. Copyright 2013 by Data Blueprint
Example: iTunes Metadata
7009/10/12
• The same:
–Interface
–Processing
–Data Structures
• are applied to
–Podcasts
–Movies
–Books
–.pdf files
• Economies of scale
are enormous
75
76. Copyright 2013 by Data Blueprint
1. Data Management Overview
2. What is metadata and why is it important?
3. Major metadata types & subject areas
4. Metadata benefits, application & sources
5. Metadata strategies & implementation
6. Metadata building blocks
7. Guiding Principles
8. Specific teachable example
9. Take Aways, References and Q&A Tweeting now:
#dataed
Outline
76
77. Copyright 2013 by Data Blueprint
1. Data Management Overview
2. What is metadata and why is it important?
3. Major metadata types & subject areas
4. Metadata benefits, application & sources
5. Metadata strategies & implementation
6. Metadata building blocks
7. Guiding Principles
8. Specific teachable example
9. Take Aways, References and Q&A Tweeting now:
#dataed
Outline
77
78. Uses
Copyright 2013 by Data Blueprint
Metadata Take Aways
• Metadata unlocks the value of data, and therefore requires
management attention [Gartner 2011]
• Metadata is the language of data governance
• Metadata defines the essence of integration challenges
Sources
Metadata Governance
Metadata
Engineering
Metadata
Delivery
Metadata Practices
Metadata
Storage
78
Specialized Team Skills
84. Copyright 2013 by Data Blueprint
Questions?
It’s your turn!
Use the chat feature or Twitter (#dataed) to submit
your questions to Peter now.
+ =
84
85. Data Systems Integration & Business
Value Pt. 2: Cloud
August 13, 2013 @ 2:00 PM ET/11:00 AM PT
Data Systems Integration & Business
Value Pt. 3: Warehousing
September 10, 2013 @ 2:00 PM ET/11:00 AM PT
Sign up here:
www.datablueprint.com/webinar-schedule
or www.dataversity.net
Copyright 2013 by Data Blueprint
Upcoming Events
85