Master%20Data%20Management%20Blending%20what%20Business%20Needs%20with%20what%20I.T.%20Needs - PowerPoint PPT Presentation

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Master%20Data%20Management%20Blending%20what%20Business%20Needs%20with%20what%20I.T.%20Needs

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... Master Data Mgmt is Master Data Management is the business processes ... responsible for developing the data stewardship strategy and visions Data ... – PowerPoint PPT presentation

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Title: Master%20Data%20Management%20Blending%20what%20Business%20Needs%20with%20what%20I.T.%20Needs


1
Master Data ManagementBlending what Business
Needs with what I.T. Needs
  • presented by Dawn MichelsInformation Architect
    of Andersen Corp.
  • Feb 21, 2007

2
Agenda
  • Defining Master Data Management
  • Three Aspects of MDM
  • Knowledge (Business Context)
  • Content
  • Maintenance
  • Business Needs vs. I.T. Expectations

3
Master Data Mgmt is
  • 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
  • Metadata
  • Tools
  • Business and Technical Processes
  • Integration of data from disparate systems

4
A couple of approaches
Source 4
Source 1
Subject Area Hub
Source 5
Source 2
Source 3
Source 6
Shareable data
5
Agenda
  • Defining Master Data Management
  • Three Aspects of MDM
  • Knowledge (Business Context)
  • Content
  • Maintenance
  • Business Needs vs. I.T. Expectations

6
Master Data Knowledge
  • Identification
  • Corporate Business Value
  • ROI
  • Data Governance Stewardship

7
Identifying Key Subjects
  • Identify where the business needs meet the
    willingness to accumulate, manage and sustain
    data
  • Examples

Customer Supplier
Product Regions
Location Corp Balance Sheet
Services
8
Business Value ROI
  • 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?

9
Data Governance
  • Data Governance Council/Executive Sponsor
  • Business Functional Management (data owner)
    responsible for the acquisition and mgmt of a key
    subject area of data on behalf of the corporation
  • Enterprise Architect
  • Technical leadership responsible for developing
    the data stewardship strategy and visions
  • Data Architect
  • Technology leadership responsible for
    implementing the data stewardship strategy,
    understanding data dependencies and relationships
    and manage the data lifecycle
  • Business Data Stewards
  • Subject Matter experts who define the business
    data definitions, process, the maintain the
    business definitions on behalf of a company
  • IT Data Stewards
  • 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
  • Employees who are authorized to create data as
    part of their jobs
  • Data Custodians
  • Employees who have the authority to govern access
    to key data areas
  • Data Users
  • Employees who have been granted authorized access
    to Company information assets to do their job.

10
Data Governance
Light
  • Data Governance Council/Executive Sponsor
  • Business Functional Management (data owner)
    responsible for the acquisition and mgmt of a key
    subject area of data on behalf of the corporation
  • Business Data Stewards
  • Subject Matter experts who define the business
    data definitions, process, the maintain the
    business definitions on behalf of a company
  • Data Custodians
  • Employees who have the authority to govern access
    to key data areas

11
Agenda
  • Defining Master Data Management
  • Three Aspects of MDM
  • Knowledge (Business Context)
  • Content
  • Maintenance
  • Business Needs vs. I.T. Expectations

12
Master Data Content
  • Metadata
  • Transformation Rules
  • Data Ownership
  • Meta Model with Relationships

Business I.T. in partnership
13
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.
  • Business
  • Business Descriptions
  • AKA ( Also Known As)
  • Business Rules
  • Valid Values
  • Semantic Layer
  • Ownership
  • Reporting
  • Data Dictionaries
  • Quality Control Rules
  • Change Control
  • Technical
  • Physical Location
  • Source to target transformations
  • Physical Characteristics
  • Key constraints
  • Indexes
  • Data Models
  • Audit Rules
  • Retention information
  • Table join recommendation
  • User Security

14
Transformation Rules
  • 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

15
Data Ownership
Role Influence Accountability
Data Steward Responsible for the acquisition and management of a key subject area of data on behalf of the Corporation Highest level of Business influence 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.
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. 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.
16
Meta Model with Relationships
Models
17
Agenda
  • Defining Master Data Management
  • Three Aspects of MDM
  • Knowledge (Business Context)
  • Content
  • Maintenance
  • Business Needs vs. I.T. Expectations

18
Master Data Maintenance
  • Defining I.T. Support Model
  • Identifying relevant measurable Metrics
  • Valid Value Rules
  • Defining a workable Roadmap

19
Defining IT Support Model
  • More than Help Desk
  • ITIL?
  • SOA?
  • SCA?
  • IEEE?

20
Master Data Subject Metrics
21
Relevant Measures
  • With the business identify what constitutes
    success
  • counts
  • quality
  • retrievability
  • Report response time?
  • Minimal Redundancy?

22
Valid Value Rules
  • Are they programmatically enforced?
  • Does I.T. or the business maintain?
  • Determine how to measure
  • Accuracy
  • Completeness
  • Consistence
  • Business Rules violation

23
Defining a workable roadmap
  • 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

24
Agenda
  • Defining Master Data Management
  • Three Aspects of MDM
  • Knowledge (Business Context)
  • Content
  • Maintenance
  • Business Needs vs. I.T. Expectations

25
MDM Business vs. I.T. Expectations
  • I.T. Needs
  • Reasonable Lead Time
  • Cost Efficiency
  • Usable across org
  • Someone to pay for the technology
  • Someone willing to define requirements
  • Business Needs
  • Speed
  • Cost Efficiency
  • Business Value
  • Competitive Advantage
  • A sense of urgency

26
Key Take Aways
  • 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!!!

27
References/Research
  • http//msdn2.microsoft.com/en-us/architecture/bb19
    0163.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,s
    id91_gci1148946,00.html excerpt on valid values
    and data strategy from Sid Adelmann and Larissa
    Moss

28
Thanks for your time and Interest!
  • 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
  • dawnmichels_at_Andersencorp.com
  • 651-264-7985

29
My background
  • 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.
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