Transcript Master Data Management - DAMA-MN

Master Data Management
Blending what Business Needs with what I.T. Needs
presented by Dawn Michels
Information Architect of Andersen Corp.
Feb 21, 2007
Agenda
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MM
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Defining Master Data Management
Three Aspects of MDM
– Knowledge (Business Context)
– Content
– Maintenance
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Business Needs vs. I.T. Expectations
MM
D – Master Data Mgmt is…
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Master Data Management is the business
processes combined with the technical
infrastructure required to provide and maintain
consistent and accurate sets of master data
It includes but is not limited to:
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Metadata
Tools
Business and Technical Processes
Integration of data from disparate systems
A couple of approaches
Source
4
Source
1
Source
2
Subject Area
Hub
Source
3
Source
5
Source
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Shareable
data
Agenda
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MM
D
Defining Master Data Management
Three Aspects of MDM
– Knowledge (Business Context)
– Content
– Maintenance
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Business Needs vs. I.T. Expectations
Master Data Knowledge
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Identification
Corporate Business Value
ROI
Data Governance & Stewardship
Identifying Key Subjects
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Identify where the business needs meet the
willingness to accumulate, manage and sustain
data
Examples:
Customer
Product
Supplier
Regions
Location
Corp Balance Sheet
Services
Business Value & ROI
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How much will a new technical solution cost?
How much will we need to make to offset
this cost?
Is it soft money or hard dollars?
Will it take a change in staff or business
processes?
Will our customers and/or users be
impacted?
Will it provide better service? Quality?
Accuracy? Customer relationship?
Data Governance
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Data Governance Council/Executive Sponsor
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Enterprise Architect
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Employees who are authorized to create data as part of their jobs
Data Custodians
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Technology delegates of the data owners or custodians who technically implement the
business data definitions and administer the technical aspect of the data asset on behalf
of the corporation
Data Creators
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Subject Matter experts who define the business data definitions, process, the maintain
the business definitions on behalf of a company
IT Data Stewards
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Technology leadership responsible for implementing the data stewardship strategy,
understanding data dependencies and relationships and manage the data lifecycle
Business Data Stewards
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Technical leadership responsible for developing the data stewardship strategy and
visions
Data Architect
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Business Functional Management (data owner) responsible for the acquisition and mgmt
of a key subject area of data on behalf of the corporation
Employees who have the authority to govern access to key data areas
Data Users
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Employees who have been granted authorized access to Company information assets to
do their job.
Data Governance
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Data Governance Council/Executive Sponsor
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Business Data Stewards
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Business Functional Management (data owner) responsible for the acquisition and mgmt
of a key subject area of data on behalf of the corporation
Subject Matter experts who define the business data definitions, process, the maintain
the business definitions on behalf of a company
Data Custodians
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Employees who have the authority to govern access to key data areas
Agenda
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MM
D
Defining Master Data Management
Three Aspects of MDM
– Knowledge (Business Context)
– Content
– Maintenance

Business Needs vs. I.T. Expectations
Master Data Content
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Metadata
Transformation Rules
Data Ownership
Meta Model with Relationships
Metadata
describes how, when and by whom a particular set of data was
collected. It also captures how the data is formatted, and if any
transformations were applied to the data along the way.
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Business
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Business Descriptions
AKA ( Also Known As)
Business Rules
Valid Values
Semantic Layer
Ownership
Reporting
Data Dictionaries
Quality Control Rules
Change Control
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Technical
– Physical Location
– Source to target
transformations
– Physical
Characteristics
– Key constraints
– Indexes
– Data Models
– Audit Rules
– Retention information
– Table join
recommendation
– User Security
Transformation Rules
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Documented changes, aggregations or adjustments
to data as it is moved from one source to target
location
Inclusions or Exclusions of information that might
be mistakenly assumed as part of a total
Agreed upon by producers as well as consumers of
the data
Data Ownership
Role
Data Steward
Influence
Responsible for the acquisition and
management of a key subject area
of data on behalf of the Corporation
Accountability
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Highest level of Business influence
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Data Custodian
Subject matter experts that define
and maintain business data
definitions and processes. Also
define and implement security
policies for business unit data.
High level of influence.
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Ensures information usage is aligned with
Corporate business strategy.
Promotes awareness and support of existing
environments.
Identifies and allocates business resources
required to implement new data acquisitions.
Approve data access and usage policies.
Identify and approve data custodians.
Subject matter experts for a given set of
business processes and definitions.
Assist in development and rationalization of
corporate business definitions and calculations.
Define and maintain business rules.
Define and maintain security classifications.
Ensure appropriate training on usage of data.
Provide data quality improvement
recommendations.
Knowledge experts for projects requiring
similar data.
Approve user access to business function data.
Prioritize enhancement requests to shared
data stores.
Meta Model with Relationships
Models
Agenda
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MM
D
Defining Master Data Management
Three Aspects of MDM
– Knowledge (Business Context)
– Content
– Maintenance

Business Needs vs. I.T. Expectations
Master Data Maintenance
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Defining I.T. Support Model
Identifying relevant measurable
Metrics
Valid Value Rules
Defining a workable Roadmap
Defining IT Support Model
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More than Help Desk
ITIL?
SOA?
SCA?
IEEE?
K
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Key Subject Areas
by Metrics
Quality
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Master Data Subject Metrics
Fair
Poor
Poor
Poor
Good
Poor
5
7
5
20
10
20
Name of
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N
Name of
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Conceptual Model Exists
Y
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N
N
Y
N
Logical Model Exists
N
N
N
N
Y
N
Physical Meta Data Exists
N
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Maintenance Standards in Place
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Analytics Available
N
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Y
N
Number of Sources
Steward or Owner Defined
Overall
Relevant Measures
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With the business identify what
constitutes success
– counts
– quality
– retrievability
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Report response time?
Minimal Redundancy?
Valid Value Rules
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Are they programmatically enforced?
Does I.T. or the business maintain?
Determine how to measure
– Accuracy
– Completeness
– Consistence
– Business Rules violation
Defining a workable roadmap
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Back to the basics
– Identify subject areas that matter to the
business
– Determine how much time, resources and
money you have to accomplish your goals
– Align the vision and execution of support
to ongoing projects in the queue
Agenda


MM
D
Defining Master Data Management
Three Aspects of MDM
– Knowledge (Business Context)
– Content
– Maintenance

Business Needs vs. I.T. Expectations
MDM – Business vs. I.T.
Expectations
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Business Needs
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Speed
Cost Efficiency
Business Value
Competitive
Advantage
– A sense of
urgency
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I.T. Needs
– Reasonable Lead
Time
– Cost Efficiency
– Usable across org
– Someone to pay
for the technology
– Someone willing
to define
requirements
Key Take Aways
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Collaboration between business and IT
essential
Identifying what Master Data Matters to your
business is critical
Determine what Governance level your
organization needs and staff accordingly
Be clear about expectations Business & I.T.
Metadata, Metadata, Metadata!!!
References/Research
http://msdn2.microsoft.com/en-us/architecture/bb190163.aspx
A good overview of MDM, with some fundamental steps
 http://www.rainingdata.com/products/soa/mdm/index.html
Challenges of Enterprise data versus Master Data mgmt
 http://www.soamag.com/I4/0207-1.asp - good article on SOA – also
see model on slide 15
 http://xml.coverpages.org/ni2005-12-07-a.html - Describes in detail
a service component architecture
 http://www.conceptdraw.com/en/sampletour/uml_erd/ (great
downloadable samples)
 http://searchcrm.techtarget.com/generic/0,295582,sid91_gci114894
6,00.html – excerpt on valid values and data strategy from Sid
Adelmann and Larissa Moss
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Thanks for your time and
Interest!
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Dawn Michels
 Enterprise Information Architect
 Past Pres DAMA-Minnesota
 Past VP Chapter Services DAMA-I
 Adjunct Faculty Member College of St.
Catherine
 Passionate Data Architect
[email protected]
651-264-7985
My background
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Dawn Michels is the Enterprise Information Architect for Andersen Corporation, in Bayport
Minnesota and has many years experience in relational database design, across several DBMS
and applications. She has developed many data designs and modeling initiatives spanning the
Insurance, Medical Devices, and Retail and Credit Card industries. Dawn has also worked for
Guidant Corporation, Fair Isaac Inc, and Minnesota Life Insurance and was the project lead at
General Mills on their first Corporate Wide DW. This included data design, internal marketing
as well as hardware and software selection. To round out her professional career, Dawn is an
adjunct faculty member at The College of St. Catherine, teaching courses in Mgmt
Information Systems and Information Mgmt. She has spoken at five previous DAMA
International Conferences on assorted topics of interest, and is scheduled to speak at DAMA-I
2007 in Boston, Mass..
Dawn was the VP of Chapter Services for DAMA International from 2000-2002. Before taking
on that role, Dawn was President of DAMA Minnesota chapter for 3 years, and VP of
Education for DAMA MN, 3 years prior to that.
She believes in sharing and mentoring to the best of her ability, as she considers the best way
to continue to develop data architecture is through experience and learning from others
experiences and networking with peers at all levels.