Title: Master%20Data%20Management%20Blending%20what%20Business%20Needs%20with%20what%20I.T.%20Needs
1Master Data ManagementBlending what Business
Needs with what I.T. Needs
- presented by Dawn MichelsInformation Architect
of Andersen Corp. - Feb 21, 2007
2Agenda
- 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
-
4A couple of approaches
Source 4
Source 1
Subject Area Hub
Source 5
Source 2
Source 3
Source 6
Shareable data
5Agenda
- Defining Master Data Management
- Three Aspects of MDM
- Knowledge (Business Context)
- Content
- Maintenance
- Business Needs vs. I.T. Expectations
6Master Data Knowledge
- Identification
- Corporate Business Value
- ROI
- Data Governance Stewardship
7Identifying 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
8Business 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?
9Data 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.
10Data 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
11Agenda
- Defining Master Data Management
- Three Aspects of MDM
- Knowledge (Business Context)
- Content
- Maintenance
- Business Needs vs. I.T. Expectations
12Master Data Content
- Metadata
- Transformation Rules
- Data Ownership
- Meta Model with Relationships
Business I.T. in partnership
13Metadata 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
14Transformation 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
15Data 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.
16Meta Model with Relationships
Models
17Agenda
- Defining Master Data Management
- Three Aspects of MDM
- Knowledge (Business Context)
- Content
- Maintenance
- Business Needs vs. I.T. Expectations
18Master Data Maintenance
- Defining I.T. Support Model
- Identifying relevant measurable Metrics
- Valid Value Rules
- Defining a workable Roadmap
19Defining IT Support Model
- More than Help Desk
- ITIL?
- SOA?
- SCA?
- IEEE?
20Master Data Subject Metrics
21Relevant Measures
- With the business identify what constitutes
success - counts
- quality
- retrievability
- Report response time?
- Minimal Redundancy?
22Valid Value Rules
- Are they programmatically enforced?
- Does I.T. or the business maintain?
- Determine how to measure
- Accuracy
- Completeness
- Consistence
- Business Rules violation
23Defining 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
24Agenda
- Defining Master Data Management
- Three Aspects of MDM
- Knowledge (Business Context)
- Content
- Maintenance
- Business Needs vs. I.T. Expectations
25MDM 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
26Key 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!!!
27References/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
28Thanks 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
29My 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.