DAS Slides: Master Data Management — Aligning Data, Process, and Governance

Copyright Global Data Strategy, Ltd. 2021
Master Data Management
Aligning Data, Process, and Governance
Donna Burbank
Global Data Strategy, Ltd.
April 22 , 2021
Follow on Twitter @donnaburbank
Twitter Event hashtag: #DAStrategies

Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2019. All rights reserved.
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Rick Jacobs | Technical Margeting Manager

Confidential and Proprietary. Do not distribute without Couchbase consent. © Couchbase 2019. All rights reserved. 2
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Thank you

05_01_16
0 5_0 1_12
OUTCOME-FOCUSED MDM
Enable Your MDM Journey
Bill O’Kan e , VP & MDM Strate g ist
Bill.OKan e @p rofise e .com
1
Strictly Con fid e n tial © 20 21P rofise e Grou p , In c.

05_01_16
Strictly Con fid e n tial © 20 21P rofise e Grou p , In c. 2
MDM Fast
Start
Ite rative
De p loym e n t
Bu sin e ss
Im p act
Road m ap
ENGAGE & ENABLE THE MDM JOURNEY
Customer Journey
Re alization of fu ll b u sin e ss valu e
Solution Platform
In d u strial stre n g th w ith fu ll fle xib ility
Engage Enable
Mu lti-Dom ain ,
Mu lti-Style
Sin g le
Cod e Base
Clou d -Native
Arch ite ctu re

05_01_16
Multi-domain/Multi-Style are required for full control with full flexibility
SOLUTION PLATFORM | MULTI-DOMAIN, MULTI-STYE
Multi-Domain, Multi-Style
on
• Any real-world business outcome touches
multiple domains
• Profisee is inherently multi-domain
• Typ ical cu stom er h as m u ltip le d om ain s
• Som e w ith u p to 10 d om ain s ru n n in g in a sin g le
p rod u ction e n viron m e n t
• ‘Most m u lti-d om ain ’ve n d or, accord in g to Gartn e r*
• The ‘right’ MDM style will change over time
• Profisee is inherently multi-style
• All MDM style s su p p orte d , in clu d in g h yb rid s
• Easy to e volve style as im p le m e n tation m atu rity
an d b u sin e ss d e m an d d e ve lop
Multiple Domain Support
Multiple Implementation Styles
Mu lti-Dom ain ,
Mu lti-Style
Sin g le
Cod e Base
Clou d -Native
Arch ite ctu re

05_01_16
‘Franken-solutions’ are more expensive, harder to learn, configure and maintain
SOLUTION PLATFORM | SINGLE CODE BASE
Single Code Base
• Consistent user experience
• Shorter learning curve
• Faster configuration
Other Vendors
Workflow Stewardship
Golden Record
Management
Event
Management
Data
Qu ality
Hie rarch y
Man ag e m e n t
Match in g
*some assembly required
Mu lti-d om ain ,
Mu lti-Style
Sin g le
Cod e Base
Clou d -Native
Arch ite ctu re

05_01_16
SOLUTION PLATFORM | PAAS: DELIVERS ON THE PROMISE OF THE CLOUD FOR MDM
Cloud-Native Architecture
• Not all cloud models work for MDM
Mu lti-d om ain ,
Mu lti-Style
Sin g le
Cod e Base
Clou d -Native
Arch ite ctu re
SaaS IaaS P aaS
Sam e h ig h cost of
m ain te n an ce (as on
p re m ise )
P ayin g for p e ak u sag e
all th e tim e
Fle xib le d ata m od e l
Un lim ite d d ata acce ss
Fast d e p loym e n t
Min im al m ain te n an ce
cost/e ffort
P ay on ly for w h at you
u se
Same architecture provides optimal delivery in cloud AND on-premise
In fle xib le d ata m od e l
Lim ite d d ata acce ss
P ayin g for p e ak u sag e
all th e tim e

05_01_16
Customer Journey
Solution Platform
Engage Enable
MDM Fast
Start
Ite rative
De p loym e n t
Bu sin e ss
Im p act
Road m ap
Mu lti-d om ain ,
Mu lti-Style
Sin g le
Cod e Base
Clou d -Native
Arch ite ctu re

05_01_16
Deliver quick wins and evolve
JOURNEY: START ANYWHERE, AND GROW...
MDM Fast
Start
Iterative
Deployment
Business
Impact
Roadmap
MDM Fast Start
• Business
• Volume-based pricing, with no domain limits
• Attractive services ratio
• Self-service training
• Technical
• Installation
• Modeling
• Batch integration
• Data Quality
• GRM
• Reporting
• Real-time integration
• Workflow
Months
Weeks
Days
Hours
Minutes
100m+

05_01_16
MDM is a journey – you need a roadmap
JOURNEY: BUILD A ROADMAP
MDM Fast
Start
Iterative
Deployment
Business
Impact
Roadmap
Business Impact Roadmap
• “Failure to use a structured framework
that delivers financial benefits…often leads
to program failure.”
• Bu sin e ss Im p a ct Roa d m a p
1. Bu ild s st a ke h old e r b u y-in
2. Develop s valu e p rioritization
• Collab oration /com m u n ication /clarification arou n d
BIR reduces program risk
#1RE
A
SON
FORM
DM
FA
IL
URE
- GA
RTNE
R

05_01_16
Quick wins: Deliver value early and often
JOURNEY: DELIVER VALUE EARLY AND OFTEN
MDM Fast
Start
Iterative
Deployment
Business
Impact
Roadmap
Iterative Deployment
• ‘The only constant is change’
• External events
• Changes in business requirements
• Changes in data sources
• Additional use cases and domains
• Evolving/tightening MDM styles
Value
Delivery
#1
ITERATE.
EVALUATE.
REPEAT.
- AGILE DEVELOPMENT
PRINCIPLES
Value
Delivery
#2
Value
Delivery
#n

05_01_16
MDM Fast
Start
Ite rative
De p loym e n t
Bu sin e ss
Im p act
Road m ap
Customer Journey
Solution Platform
Engage Enable
Mu lti-Dom ain ,
Mu lti-Style
Sin g le
Cod e Base
Clou d -Native
Arch ite ctu re

05_01_12
Strictly Con fid e n tial © 20 21P rofise e Grou p , In c.

Global Data Strategy, Ltd. 2021
Donna Burbank
2
• Recognized industry expert in information
management with over 25 years of
experience in data strategy, information
management, data modeling, metadata
management, and enterprise architecture
• Managing Director at Global Data Strategy,
Ltd., an international information
management consulting company that
specializes in the alignment of business
drivers with data-centric technology
• Worked with dozens of Fortune 500
companies worldwide in the Americas,
Europe, Asia, and Africa and speaks
regularly at industry conferences
• Excellence in Data Management Award
from DAMA International
• Past President and Advisor to the DAMA
Rocky Mountain chapter
• Co-author of several books on data
management
• Regular contributor to industry
publications
• She can be reached at
donna.burbank@globaldatastrategy.com
Donna is based in Boulder, Colorado, US
Follow on Twitter @donnaburbank
@GlobalDataStrat

DATAVERSITY Data Architecture Strategies
• January Emerging Trends in Data Architecture – What’s the Next Big Thing?
• February Building a Data Strategy - Practical Steps for Aligning with Business Goals
• March Data Modeling Case Study – Business Data Modeling at Kiewit
• April Master Data Management – Aligning Data, Process, and Governance
• May Data Architecture, Solution Architecture, Platform Architecture – What’s the Difference?
• June Enterprise Architecture vs. Data Architecture
• July Best Practices in Metadata Management
• August Data Quality Best Practices (with guest Nigel Turner)
• September Data Modeling Techniques
• October Data Governance: Aligning Technical & Business Approaches
• December Data Architecture for Digital Transformation
3
This Year’s Lineup

What We’ll Cover Today
• Master Data Management (MDM) provides organizations with an accurate and
comprehensive view of business-critical data such as Customers, Products, Vendors, and
more.
• While mastering these key data areas can be a complex task, the value of doing so can be
tremendous – from real-time operational integration to data warehousing & analytic
reporting.
• This webinar provides practical strategies for gaining value from your MDM initiative, while
at the same time assuring a solid architectural and governance foundation that will ensure
long-term, enterprise-wide success.
4

A Successful Data Strategy links Business Goals with Technology Solutions
Level 1
“Top-Down” alignment with
business priorities
Level 5
“Bottom-Up” management &
inventory of data sources
Level 2
Managing the people, process,
policies & culture around data
Level 4
Coordinating & integrating
disparate data sources
Level 3
Leveraging data for strategic
advantage
Master Data is Part of a Wider Data Strategy

What is Master Data?
• Master Data is the consistent and uniform set of identifiers and extended attributes that
describes the core entities of the enterprise including customers, prospects, citizens,
suppliers, sites, hierarchies and chart of accounts (sic).
• Master data management (MDM) is a technology-enabled discipline in which business
and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency and
accountability of the enterprise's official shared master data assets.
- Source Gartner
6
Definition

Master Data
7
From Data Modeling for the Business by Hoberman, Burbank, Bradley, Technics Publications, 2009
Master Data is often the most critical data of the organization –
and the most intuitive for business users to grasp.
Early Master Data

8
Real-world examples
The “dead” living organism
The $1M cheese slice The $2M baby bottle
Which Dr. Smith is credentialled
for heart surgery?
Which Michael Jones is the
high-net worth customer?
How do we define Regions, Markets,
Locations, Catchments, Sites, etc.?

9
Real-world examples

Understanding Your Customer
10
A 360 Degree View through Data
Stefan Krauss
Age = 31
Occupation = Ski Instructor Purchased €500 in
outdoor gear in 2015
100% of purchases online
Top Finisher in Engadin Ski
Marathon 2010-2015
Member of Loyalty
Program since 2010
Prefers Text Message
Address = Pontresina, Switzerland

11
Stefan Krauss
Age = 62
Understanding Your Customer
A 360 Degree View through Data
Occupation = Banker
Member of Loyalty
Program since 1990
Football Fan
Prefers Physical Mail
100% of spending in store
75% of spending is while
on holiday
Purchased €3.500 in
outdoor gear in 2019
Address = Zurich, Switzerland

Master Data
Management
Data
Architecture
Data
Governance &
Stewardship
Business
Process
Alignment
• Accountability & stewardship
• Business rule validation
• Conflict resolution
• Business Prioritization
• Business process models
• Data mapping to process
• CRUD and usage matrices
• Optimizing business process
for data improvement
• System Architecture & data flow
• Data models & hierarchies
• Match/merge and survivorship rules
• Data integration & design
Successful MDM Combines Data, Process, and Accountability

Customer Date Product Code Price Quantity Location
Stefan Kraus 1/2/2017 Scarpa Telemark Ski Boot SC1279 €250 1 St. Moritz, CH
Donna Burbank 1/5/2017 Scarpa Telemark Ski Boot SCU1289 $150 1 Boulder, CO
Stefan Kraus 1/2/2017 North Face Down Jacket NF8392 €450 1 Zurich, CH
Stefan Kraus 1/2/2017 Garmin Sports Watch GM29384 €200 2 Zurich, CH
Wendy Hu 3/4/2017 Prana Yoga Pant PN82734 $51 5 New York, NY
Joe Smith 4/1/2017 Garmin Sports Watch GM29384 $150 1 Albany, NY
Transaction Data vs. Master Data
13
Master Data:
Customer
Master Data: Product
Master Data: Location
Reference Data:
Country Codes
Reference Data:
State Codes
Transaction
Data

What is Master Data? What is Reference Data?
14
How do we define Regions, Markets,
Locations, Catchments, Sites, etc.?
One person’s Master Data is
another person’s Reference Data… vs.
Address Line 1
Address Line 2
City
State
AL
AK
AR
AZ
CA
CO
..etc.
Master Data Reference Data

ETL
Master Data Overview
15
CRM In-Store
Sales
Marketing
Finance Online
Sales
Supply
Chain
MDM
“Golden Record”
Data
Warehouse BI & Reporting
Data Model
Lookup
End User Applications
Reference
Data Sets
Data Quality
& Matching
Publish & Subscribe
Data Stewardship
Validation

ETL
16
CRM In-Store
Sales
Marketing
Finance Online
Sales
Supply
Chain
Each system has its own unique
functionality and associated data model.
MDM
“Golden Record”
Data
Data Model
Lookup
Reference
Data Sets
Data Quality
& Matching
Publish & Subscribe
Data Stewardship
Validation
First Name
Family Name
Address Line 1
Address Line 2
City
State
Phone
Email
Spouse
First Name
Postal Code
Customer ID
First Name
Family Name
Account #
Credit Balance
First Name
Middle Name
Family Name
Email
Twitter ID
Gender
First Name
Family Name
Address Line 1
Address Line 2
City
State
Credit Card #
Phone
First Name
Family Name
Address Line 1
Address Line 2
City
State
Country
Phone

ETL
17
CRM In-Store
Sales
Marketing
Finance Online
Sales
Supply
Chain
MDM
“Golden Record”
Data
Data Model
Lookup
Reference
Data Sets
Data Quality
& Matching
Publish & Subscribe
The MDM data model is a selected
super/subset of the source system models.
Data Stewardship
Validation
Customer ID
First Name
Family Name
Address Line 1
Address Line 2
City
State
Country
Phone
Email
Country Codes
State Codes
First Name
Family Name
Address Line 1
Address Line 2
City
State
Phone
Email
Spouse
First Name
Postal Code
Customer ID
First Name
Family Name
Account #
Credit Balance
First Name
Middle Name
Family Name
Email
Twitter ID
Gender
First Name
Family Name
Address Line 1
Address Line 2
City
State
Credit Card #
Phone
First Name
Family Name
Address Line 1
Address Line 2
City
State
Country
Phone

ETL
18
CRM In-Store
Sales
Marketing
Finance Online
Sales
Supply
Chain
MDM
“Golden Record”
Data
Data Model
Lookup
Reference
Data Sets
Publish & Subscribe
Data Stewardship
Validation
First Name = John
Family Name = Smith
Address Line 1 = 101 Main ST
Address Line 2
City = Anywhere
State = Texas
ZIP = 10101
Phone = 555 927 1212
Email = johns@gmail.com
Spouse = Mary
First Name = Jack
Postal Code = 10101
Customer ID = 123
First Name = John
Family Name = Smith
Account #
Credit Balance
First Name = J.
Middle Name
Family Name = Smith
Email = goaway@me.net
Twitter ID = @johns
Gender = Male
First Name = Johnn
Family Name
Address Line 1 = 101 Main Street
Address Line 2 = Apt 2
City = Plano
State = TX
Credit Card #
Phone = +1 555 927 1212
First Name = John
Family Name = Smith
Address Line 1 = 101 Main St
Address Line 2
City = Anywhere
State = TX
Country = USA
Phone = x1212
Customer ID = 123
First Name = John
Family Name = Smith
Address Line 1 = 101 Main ST
Address Line 2 = Apt 2
City = Anywhere
State = TX
Postal Code = 10101
Country = USA
Phone = +1 555 927 1212
Email = johns@gmail.com
Matching Rules help create a
“Golden Record”
Data Quality
& Matching

ETL
19
CRM In-Store
Sales
Marketing
Finance Online
Sales
Supply
Chain
MDM
“Golden Record”
Data
Data Model
Lookup
Reference
Data Sets
Data Quality
& Matching
Publish & Subscribe
Applications can reference
the “Golden Record” for
lookup.
Data Stewardship
Validation

ETL
20
CRM In-Store
Sales
Marketing
Finance Online
Sales
Supply
Chain
MDM
“Golden Record”
Data
Data Model
Lookup
Reference
Data Sets
Data Quality
& Matching
Publish & Subscribe
MDM can feed the dimensional model for
the data warehouse (e.g. customer,
location, etc.)
Data Stewardship
Validation

MDM is not Reporting or Analytics
-- It can be a Source
21
MDM
“Golden Record”
Data
e.g. Customer by Region
Reference
Data Sets
Graph Database
Social Network
Analysis
Data Lake
Social Media
Sentiment Analysis

ETL
22
CRM In-Store
Sales
Marketing
Finance Online
Sales
Supply
Chain
MDM
“Golden Record”
Data
Data Model
Lookup
Reference
Data Sets
Data Quality
& Matching
Publish & Subscribe
“Human in the Loop” – Data
Stewards can validate match
candidates.
Data Stewardship
Validation

Governance & Business Process for MDM
• While the implementation of the hub and population strategies is complex, more
complex is understanding the business processes and governance processes
around the populating and publishing systems.
• In fact, the top two reasons for failure of MDM systems cited by the Gartner
analyst group1 are :
23
1 Top Four Reasons Your MDM Program Will Fail, and How to Avoid Them, Gartner, 2016, ID:
G00223675, by Bill O’Kane. Note: The remaining two reasons are: Failure to Manage Initial Master
Data Quality & Defining Transactional (Fact) Data as Master Data
Failure of IT to Align With
Business Process Improvements
and Document Business Value
Delaying or Mismanaging
Information Governance
Implementation

Data Architect*
Data Governance Roles
24
Executive Sponsor Business Data Owner Business Data Steward Technical Data Steward
Data Governance Lead*
• Promotes Data Driven Culture
• Champions Best Practices
• Advocate with ELT and Board
• Escalation Point for Key Issues
• Represents the data needs for a
particular functional area
• Defines key KPIs & data elements
• Defines key business rules
• Sets Data Quality Metrics &
Thresholds
Data Security Lead*
• Acts as a cross-functional lead for the data governance effort, working with both business and IT roles
• Chair of the Data Governance Steering Committee
* Typically a full-time role
• Responsible for the day-to-day
management and quality of data
• Subject Matter Expert (SME) for
a given business domain
• Aligns with the Data Owner to
support business rules and to
align with key KPIs
• Oversees the holistic data architecture for the organization, including data models, data standards, data integration, etc.
• Works with both business and technical stakeholders to ensure that systems implementations align with key business rules & needs
• Ensures that the organization adheres to the adequate security standards to support industry regulations and best practices
• Works with the Data Governance Lead and Data Architecture to ensure that data implementations support business needs in a secure way.
• Digital/IT expert for a given
business unit
• Subject matter expert for a given
system and its usage
• Aligns with Business Data
Stewards to ensure technical
needs are met

5 Models of Data Governance & Stewardship
Model Description
Process Centric
Process owner(s) become(s) the data owner for all data created, amended & deleted by the business
process for which they are responsible (e.g. Claims process, Billing process, etc.)
Systems Centric
System owner(s) become(s) the data owner for all data created, amended & deleted by the IT system
for which he / she is responsible (e.g. CRM, Billing System, etc.)
Data Domain
Centric
Business appointed roles accountable for improvement of key data domains, created, stored or used
across an organization (e.g. Patient, Student, Product, Customer, etc.)
Organization
Centric
Business appointed roles accountable for improvement of key data domains on the basis of
departmental boundaries (e.g. Finance, Marketing, Clinical, etc.) or geographical locations.
Blended
In large and complex organizations, an overall Data Governance program may consist of combinations
of some or all of the above models
25
There are diverse ways to implement data stewardship, unique to each organization.

Conceptual Data Model
26
Supporting Data Domain-centric Governance
Conceptual Data Models are helpful
tools in identifying key master and
reference data domains.

The Importance of Business Process
• Process models are a helpful tool for describing core business processes (e.g. BPMN).
• “Swimlanes” outline organizational considerations
• Data can be mapped to key business processes to understand creation & usage of information (CRUD Matrix)
• Understanding business process is critical to Master Data & related Data Governance
• Who is using data?
• How is it used in business processes?
• Are there redundancies, conflicts, etc.?
27
Identifying key data dependencies in core business processes
Customer Order Account Invoice Product
Receive Customer Order R C C, R
Process Customer Order C,R,U R,U R
Fill Order R,U R,U R,U
Send Invoice R,U R,U C
CRUD Matrix
Business Process Model

Organizational or Capability – Based Approach
28
A Comprehensive View of Data Across the Enterprise
Sales
Data Governance Committee
Marketing
Product
Development Legal
HR Analytics
Supply
Chain
Finance
An Organization or Capability-centric approach
helps gain cross-functional input for data decisions.
Who “owns” Customer, Patient, Student, Product,
Ingredient, Component, Brand, etc…?

Optimizing Restaurant Revenue through Menu Data
• An international restaurant chain realized through its digital strategy that:
• While menus are the core product that drives their business…
• They had little control or visibility over their menu data
• Menu data was scattered across multiple systems in the organization from supply chain to kitchen prep to marketing,
restaurant operations, etc.
• Menu data was consolidated & managed in a central hub:
• Master Data Management created a “single view of menu” for business efficiency & quality control
• Data Governance created the workflow & policies around managing menu data
• Process Models & Data Mappings were critical
• Business Process diagrams to identify the flow of information
• CRUD Matrixes to understand usage, stewardship & ownership
Managing the Data that Runs the Business
Product Creation &
Testing
Menu Display &
Marketing
Supply Chain Point of Sale &
Restaurant Operations
www.globaldatastrategy.com

Summary
30
• Interest in Master Data Management (MDM) is on the rise as more organizations look to gain a
common, consistent source for their core data assets (Customer, Product, Supplier, Employee, etc.)
• Successful MDM is part of a wider data strategy and requires integration with:
• Data Architecture
• Business Process Alignment
• Data Governance & Stewardship
• Getting this combination right can have a positive impact on the success of the business.

DATAVERSITY Data Architecture Strategies
• January Emerging Trends in Data Architecture – What’s the Next Big Thing?
• February Building a Data Strategy - Practical Steps for Aligning with Business Goals
• March Data Modeling Case Study – Business Data Modeling at Kiewit
• April Master Data Management – Aligning Data, Process, and Governance
• May Data Architecture, Solution Architecture, Platform Architecture – What’s the Difference?
• June Enterprise Architecture vs. Data Architecture
• July Best Practices in Metadata Management
• August Data Quality Best Practices (with guest Nigel Turner)
• September Data Modeling Techniques
• October Data Governance: Aligning Technical & Business Approaches
• December Data Architecture for Digital Transformation
31
This Year’s Lineup

Who We Are: Business-Focused Data Strategy
Maximize the Organizational Value of Your Data Investment
In today’s business environment, showing rapid time to value for
any technical investment is critical.
But technology and data can be complex. At Global Data Strategy,
we help demystify technical complexity to help you:
• Demonstrate the ROI and business value of data to your
management
• Build a data strategy at your pace to match your unique culture
and organizational style.
• Create an actionable roadmap for “quick wins”, which building
towards a long-term scalable architecture.
Global Data Strategy’s shares experience from some of the largest
international organizations scaled to the pace of your unique team.
www.globaldatastrategy.com
Global Data Strategy has worked with organizations globally in the
following industries:
Finance · Retail · Social Services · Health Care · Education · Manufacturing
· Government · Public Utilities · Construction · Media & Entertainment ·
Insurance …. and more

Global Data Strategy, Ltd. 2021 www.globaldatastrategy.com
Questions?
Thoughts? Ideas?
33

DAS Slides: Master Data Management — Aligning Data, Process, and Governance

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DAS Slides: Master Data Management — Aligning Data, Process, and Governance