Master+Data+Managementsdfdsfsdfdsfsd.pdf

to The Complete Master Data Management Masterclass
Presentation by George Smarts for Udemy

What will you learn in this course?
Module 1 - The Basics
Module 2 - Types of Master Data
Module 3 - Managing Master Data
Module 4 - MDM Roles
Module 5 - MDM Implementation Models
Module 6 - Master Data Management Tools
Module 7 - Best Practices for MDM
Module 8 - MDM Maturity
Module 9 - Steps to Implement MDM
Module 10 - Future Trends in MDM

Why take this course?
Reason 1 - We cover Master Data Management fully
Reason 2 - Real examples of use cases
Reason 3 - Tips and tricks from experience
Reason 4 - Answers most questions that you can expect in interviews
Reason 5 - Gain conﬁdence in attending any data meeting
Reason 6 - Additional resources provided for further reading

Download the course resources
Main resource - PDF Presentation ﬁle with all lessons
Other resources - additional resources/reading materials provided in
various lessons

What is Master Data
DAMA Guide to Data Management Body of Knowledge: “Master Data represents data
about the business entities that provide context for business transactions”
Gartner: “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”

What is Reference Data
DAMA Guide to Data Management Body of Knowledge: “Reference data is data used to
classify or categorize other data”
Examples of Reference Data:
● Postal codes
● Language codes
● Customer segments
● Country codes
● Cost centers

Master Data vs Reference Data
Comparison Master Data Reference Data
Main purpose Represents the business objects which
contain the most valuable, agreed upon
information shared across the
organization
Data that defines the set of permissible
values to be used by other data fields
More on usage Master data is the data shared by multiple
systems, applications, processes in the
organization
Reference data is a type of master data
that is used by other data fields
Examples ● Customer information - names,
phone numbers and addresses
● Product information - product
name and location
● Partner data - partner name and
address
● Fixed conversion rates - weight,
temperature, length, etc
● Currency codes
● Language codes
● Customer Segments
● Cost centers
● Postal codes
● Units of measurement

What is Master Data Management (MDM)
Master Data Management is the process of creating and maintaining a single
master record - or single source of truth - for each person, place, and thing in a
business.
Through MDM, organizations gain a trusted, current view of key data that can be
shared across the business and used for better reporting, decision-making, and
process eﬃciency.
Source - deﬁnition SAP. www.sap.com/insights/what-is-master-data-management-mdm

Why MDM is important
Improves Data
Quality
Improves Decision
Making
Reduces Time to Market
Data Compliance &
Governance
Improves Business
Process Efﬁciency
Eliminates Manual
Processes
MDM
Reduces Workload

MDM Challenges
Data Quality
Data Integration
Data Governance
ROI (Return on Investment)
Resistance to Change
Scalability
MDM

Module 2 - Types of Master Data

Customer Master Data
What is it
Customer MDM is all about collecting, consolidating, maintaining and
distributing customer data in the organization.
- Demographics data
- Transactional data
- Behavioral data
Why is it important
● Better customer insights
● Improved customer experience
● Better data governance on customer data, especially important for
sensitive information
Example
Let’s say you have an ecommerce store that sells products in 100+ different
categories. Customer master data management allows you to identify appropriate
target segments to promote to your customers.
E.g. you will offer them discounted or products on offer for categories where you see
they have bought before before or expressed interest in another engagement such as
surveys, etc

Product Master Data
What is it
Product MDM is all about collecting, consolidating, maintaining and distributing data
about the company products and its characteristics.
This is information such as product name, product number, description, weight,
dimensions, material, manufacturer, supplier, etc.
Why is it important
● Better supply chain management
● Better decision-making
● Better customer experience
● Compliance with regulations
Example
If you are producing food products, you need to comply with all regulations by the FDA (Food
and Drug Administration). Some of these regulations include things such as that the products
need to be labeled with accurate and up-to-date information on ingredients, etc.
With Product MDM you can automate and centralize the management of product information on
labels.

Financial Master Data
What is it
Financial MDM is all about collecting, consolidating, maintaining and distributing
data about the company finances.
This is information such as tax information, price, cost, profit, currency, exchange
rates,etc
Why is it important
● Reduce manual processing of financial data
● Better decision making on pricing
● Compliance with regulations
Example
Many companies without Master Data Management face challenges with their financial reporting
due to inconsistent data that sits in silos across the different departments and locations.
This makes is extremely difficult to accurately report at WW level on sales, profit, margins, etc.
This also becomes a legislation issue if for example the company is publicly traded company.

Partner Master Data
What is it
Partner MDM is all about collecting, consolidating, maintaining and distributing data
about the company business partners.
This is information such as suppliers information, distributors information, etc
Why is it important
● Better decision making on partner relationships
● Better partner collaboration
● Better efficiency
Example
Many companies store partner data on multiple systems and local solutions such as
spreadsheets. This leads to a lot of issues with errors, duplications, time spent on finding the
information, etc
An MDM solution will help to centralize and standardize such information which leads to a lot of
benefits by having all partner data in one single place with proper data governance.

Employee Master Data
What is it
Employee MDM is all about collecting, consolidating, maintaining and distributing
data about the company employees within the organization.
This is information such as personal details, contract information, beneﬁts, job title,
etc
Why is it important
● Centralized and governance repository of sensitive information
● Automate HR processes
● Compliance with legal requirements on handling employee data
Example
A large company with locations in multiple countries and no MDM solution will likely have
multiple systems and processes for handling employee data.
This can lead to inconsistencies and inaccurate information. This makes it extremely difﬁcult for
leadership to quickly access data about employees and make informed decisions fast. This can
also lead to potential legislation issues since it only takes one mistake from one HR employee
for the data to be sent to the wrong place, overwritten, etc.

Other Types of MDM data
● Location master data
● Asset master data
● Many more possible

Module 3 - Managing Master Data

Managing master data
Data Collection Data Validation Data Integration Data Enrichment Data Distribution
Data Governance,
Access and Security
Data
Maintenance
Step 1 Step 2 Step 3 Step 4 Step 5 Step 6 Step 7
Data Analytics
and Reporting
Data Monitoring
and QA
Step 8 Step 9

MDM Key Roles
MDM Program
Manager
Master Data
Specialist Data Steward
Other Data
Experts
Executive
Sponsor
Presentation by George Smarts
Source: https://www.techtarget.com/searchdatamanagement/definition/master-data-management
Business
stakeholders
● Overall responsible for MDM implementation
● Coordinates all activities
● Reports on progress to leadership
● Helps MDM Program Manager with all tasks
● Responsible for creation and maintenance of master data
● Technical knowledge of the MDM Solution and data
● Responsible to oversee the data for specific data domain
● Define the data standards and enforce data governance
● Act as SME for their data domain
● Data Integration Specialists
● Data Architect
● IT Infrastructure Manager
● And more
● Senior-level executive that gives green light to the MDM program
● Promotes the MDM program across the company
● Aligns the MDM program to the organization strategic goals
● Department Leads that are impacted by the MDM program
● Participates in steering committee
● Provide approvals for changes affecting their department

Module 5 - MDM Implementation Styles

Module 6 - Master Data Management Tools

What are some of the best MDM tools?

Module 7 - Best Practices for MDM

MDM Best Practices
Align MDM Goals with
Company Goals
Data Governance is
key
Keep watch on the
latest trends
Focus on simplicity
and scalability
Involve business
stakeholders in the
MDM process
Deﬁne ownership
and accountability
MDM

Module 9 - Steps to Implement MDM

Steps to implement MDM
Learn about MDM:
● Important Capabilities
● Implementation Styles
● Domain Categories
Analyze your current
data environment
Deﬁne your business
goals
Secure the right
sponsorship
Repeat Step 6 and
monitor
Get the right team and
tool
Implement a
quick win

MDM Solution Capabilities
● Workﬂow/BPM
● Loading/Sync/Business Services
● Data Modeling
● Information Quality/Semantics
● Perform/Scale/Availability/Security
● Hierarchy Management
● Data Stewardship
● Data Governance
● Multiple Implementation Styles
● Multiple Usage Scenarios
● Multiple Domain and Multidomain
● Product Suite Internal Integration
MDM Capabilities
Source: Gartner - Critical Capabilities for Master Data Management Solutions

MDM Domains
Product Domain
Location Domain
Digital Assets
Customer Domain
Supplier Domain
Other
MDM

Learn about MDM:
Important Capabilities
Implementation Styles
Domain Categories
data environment
goals
Secure the right
sponsorship
Repeat Step 6 and
monitor
tool
Implement a
quick win
1. What are the different company departments?
2. What kind of data do they use?
3. Where is the data coming from?
4. Is it well integrated with the company tools/apps and
central repositories?
5. Any data silos?
6. What are the main data problems for the business?
7. Are there data quality controls in place?
8. How is the data being governed?
9. Who are the main data stewards in the department?
10. Any documentation that will help the MDM program?

Learn about MDM:
Domain Categories
data environment
goals
Secure the right
sponsorship
Repeat Step 6 and
monitor
tool
Implement a
quick win
Some business drivers for MDM include:
● Up sell and cross sell opportunities
● Complete view of customers
● Improved Data Quality and business decisions
● Centralization of data
● Reduce costs of data maintenance and support
● Improved customer experience
● Other

Learn about MDM:
Domain Categories
data environment
goals
Secure the right
sponsorship
Repeat Step 6 and
monitor
tool
Implement a
quick win
● MDM Programs can take years to implement
● Present your goals, strategy and success criteria
● Go to the top for long term budget commitment

Learn about MDM:
Domain Categories
data environment
goals
Secure the right
sponsorship
Repeat Step 6 and
monitor
tool
Implement a
quick win
Get the Right Team:
● Business Team - *Sponsor (already covered), business analysts/SME, end
users/data stewards
● Program Team - MDM Specialist, Data Architects, Program Manager
● Tech Team - DBA, Developers, Integration Experts, System Admins

Learn about MDM:
Domain Categories
data environment
goals
Secure the right
sponsorship
Repeat Step 6 and
monitor
tool
Implement a
quick win
Get the Right MDM Solution (Master data management software that consists of policies,
governance, standard tools and processes that facilitate deﬁning and managing organization’s data from
a single point):
1. Understand your needs - features, functionality and business processes
2. Make a list of top 3-4 MDM solutions to further explore
3. Explore with a free trial

Learn about MDM:
Domain Categories
data environment
goals
Secure the right
sponsorship
Repeat Step 6 and
monitor
tool
Implement a
quick win
● Start with a small pilot project to show the power of MDM (look for the
stakeholders that were vocal about their data problems in Step 2)
● Leads to your ﬁrst happy customers
● Secures your budget for the long term

Learn about MDM:
Domain Categories
data environment
goals
Secure the right
sponsorship
Repeat Step 6 and
monitor
tool
Implement a
quick win
● Maintain the long term vision and release “wins” at regular intervals
● Keep on tracking the KPIs
● Maintain leadership’s interest in the MDM Program

Module 10 - Future Trends in MDM

Future Trends of MDM
AI and ML
Data Privacy and
Compliance
IoT (Internet of Things)
Move to the cloud
Top 5
Future Trends Collaboration

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