This document provides an overview of the Data Management Maturity (DMM) model and its ecosystem. It introduces the presenters and describes the development of the DMM model over 3.5 years with input from 50+ authors and 70+ peer reviewers. The DMM is designed to help organizations evaluate and improve their data management capabilities through a structured assessment and benchmarking approach. It describes the DMM structure, levels, and themes and outlines upcoming certification programs, products, and events to support widespread adoption of the DMM model.

1. DMM Case Study: Ally
January 27, 2015

2. 2
Presenters
Melanie Mecca
Program Director, DMM Products & Services
• Development lead and primary author, Data
Management Maturity Model
• Led creation of DMM certification courses
and Assessment method
• 30+ years DM solutions, strategy, program
implementation
• Certified EDM Expert
Leslie Burgess
Senior Manager, Enterprise Data Governance
• Responsible for overseeing Ally Critical
Element engagements across enterprise
• Support development of Data Management
practices into Line of Business procedures
• Led establishment of Basel II Data Control
Framework
• 20+ years IT Project Management,
Strategic Planning and BP Reengineering

3. 3
CMMI – Worldwide Process Improvement
CMMI Quick Stats:
• Over 10,000
organizations
• 94 Countries
• 12 National
governments
• 10 languages
• 500 Partners
• 1600+
Appraisals in
2014

4. 4
Data Management Maturity (DMM)SM Model
The DMM was released on
August 7, 2014
• 3.5 years in development
• 4 sponsoring organizations
• 50+ contributing authors
• 70+ peer reviewers
• 80+ organizations involved
• 300+ practice statements
• 500+ functional work products

5. 5
DMM Drivers
• Effective data management programs require a planned strategic effort
• Data is the infrastructure foundation of the n-tier architecture
• Integrate multi-discipline, multi-business line efforts
• Inculcate a shared vision and understanding
• Not a Project, and more than a Program – a lifestyle.
• Organizations needed a comprehensive reference model to evaluate
capabilities and measure improvements – benchmark and guidance
• DMM targeted to unify understanding and priorities of lines of
business, IT, and data management. Aimed at the biggest challenges:
• Achieving an organization-wide perspective
• Alignment of IT/DM with the business
• Clear communications with the business
• Sustaining a multi-year effort with energy and impact.

6. 6
Foundation for advanced solutions
You can accomplish Advanced Data
Solutions without proficiency in
Basic Data Management Practices,
but solutions will:
• Take longer
• Cost more
• Not be extensible
• Deliver less
• Present
greater
risk
6Copyright 2013 by Data Blueprint
Fundamental Data Management Practices
Advanced
Data
Solutions
• MDM
• Analytics
• Big Data
• IOT
• Warehousing
• SOA
6
Data Management Function
Data Management Strategy
Data Governance
Data Quality Program
Data Integration
Metadata Management

7. 7
DMM Themes
• Architecture and technology neutral – applicable to legacy, DW, SOA,
unstructured data environments, mainframe-to-Hadoop, etc.
• Industry independent – usable by every organization with data
assets, applicable to every industry
• Emphasis on current state – organization is assessed on the
implemented data layer and existing DM processes
• Launch collaborative and sustained process improvement – for the
life of the DM program [aka, forever].
If you manage data, the DMM can benefit you

8. 8
DMM Structure

9. 9
DMM Capability Levels
Performed
Managed
Defined
Measured
Optimized
Level
1
Level
2
Level
3
Level
4
Level
5
Risk
Quality
Ad hoc
Reuse

10. 10
DMM Assessment Summary
Sample Organization

11. 11
2015 – Building the DMM Ecosystem
Results / Assets
Partner Program
/ Outreach
Certifications
Product
Suite
DMM

12. 12
DMM Ecosystem - Product Suite
Results / Assets
Partner Program
/ Outreach
Certifications
Product
Suite
DMM
• DMM Introduction – learn about
DMM concepts
• DMM Intro eLearning – self-
paced study
• DMM Advanced Concepts –
learn how to interpret the DMM
• Enterprise Data Management
Expert – learn to assess
organizations with the DMM and
implement programs
• DMM Lead Appraiser – learn to
benchmark organizations against
the DMM

13. 13
DMM Ecosystem - Certifications
Results / Assets
Partner Program
/ Outreach
Certifications
Product
Suite
DMM
Certifications:
Credentials and Credibility
• Enterprise Data Management
Expert (EDME) – Assessing and
Launching the DM Journey
• DMM Lead Appraiser (DMM LA)
– Benchmarking and Monitoring
Improvements

14. 14
DMM Ecosystem – Partner Program
Results
Reporting
Partner Program
/ Outreach
Certifications
Product
Suite
DMM

15. 15
DMM Ecosystem – Results and Assets
Results / Assets
Partner Program
/ Outreach
Certifications
Product
Suite
DMM
Results
• Benchmarking
• Web publication of approved
appraisals
• Case studies
• Best Practice Examples
DMM Assets
• White Papers
• Seminars
• Profiles
• Academic Courses

16. 16
When Should I Employ the DMM?
• Use Cases - assess current capabilities before:
• Developing (or enhancing) your DM program / strategy
• Embarking on a major architecture transformation
• Establishing data governance
• An expansion of analytics – e.g. ambitious new program
• Implementing a data quality program
• Implementing a metadata repository
• Designing and implementing multi-LOB solutions:
• Master Data Management
• Shared Data Services
• Enterprise Data Warehouse
• Conversion to an ERP
• Other major efforts, etc. Like an Energy audit!

17. 17
Events – Feb through Jun 2015
• Series of white papers - DataVersity
• DMM Intro – Mar 25-27 DC – before DAMA EDW conference
• eLearning DMM Intro - Apr
• EDME – Apr 13-17 DC
• Enterprise Data World Mar 30 – Apr 2
• DMM Seminar with Peter Aiken
• DMM Case Studies – Freddie Mac and FRS Statistics
• DGIQ – Jun 8-11 – Data Quality with the DMM
• DMM Intro – May 13-15 Seattle – with CMMI Global
• DMM Intro – Jun 6-8 Dublin
• DMM Advanced – May / Jun

18. 18
The DMM Helps an Organization!
Gradated path -
step-by-step
improvements
Unambiguous
practice
statements for
clear
understanding
Functional work
products to aid
implementation
Common language
Shared
understanding of
progress
Acceleration