This document discusses master data management. It defines master data as critical business data that is cleaned, reliable, and secured. Master data is integrated into a single system of record with a single version of truth. The document discusses why companies implement master data management - to locate critical data in one place, reduce maintenance costs, and increase data quality. It also outlines different approaches to architecting master data, including centralized, co-existence, consolidation, and virtual architectures. The advantages and uses of each architecture are compared.

1. ( Big ) Data Management
Master Data
Global Concepts in 10 slides
2016
Nicolas SARRAMAGNA
https://fr.linkedin.com/pub/nicolas-sarramagna/19/941/587

2. CONTENTS
 Introduction
 What / Why
 How
 References

3. COMPAGNIE PLASTIC OMNIUM
CONFIDENTIAL
Master Data in Data Management 3
 DATA MANAGEMENT
 Multiples modules
 BIG DATA
 Velocity, Volume, Variety, Veracity, Value
Collect
Storage
Data Mining /
Machine Learning
Data Viz
Governance
Security
Master Data
Data quality

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Master Data – What / Why 4
 MASTER DATA = VERACITY
 Business cross data dispersed in the enterprise
 Data cleaned, reliable, secured
 Data integrated in a system of records (single version of truth) and delivered as a service. Named golden record
in the master source.
 Examples of Master Data :
 parties (customers, suppliers, partners, …)
 things (products, bank accounts, prices list), places (locations, postal codes, plants, subsidiaries, zones)
 hierarchical links (cost center, job families, …)
 Note : transactional data = fact with time -> not a MD
 MASTER DATA MANAGEMENT
 Deliver process, tools, governance to build and maintain master data
 Master Data + Governance + usage of Data Quality -> MDM
 WHY
 Locate in one place and reduce maintenance of the data used by multiple applications
 Increase data quality and security on cross and critical data
 Expose these data for new usages and services
 DATA BELONGS TO THE COMPANY NOT TO A BUSINESS

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Master Data – How 5
 APPROACH TO PUT IN PLACE EACH MASTER DATA (1/2)
 Current map of this data in the SI + define the master data  try to fill the Master Data Sheet.xlsx
 For each block, fill ‘Today’ and ‘Tomorrow’

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Master Data – How 6
 APPROACH TO PUT IN PLACE EACH MASTER DATA (2/2)
 Elaborate the architecture for this MD
 Build the MCD in the MDM tool
 Connect producers
 Perform data quality
 Connect consumers
 Make a communication
 Maintain the master data : business, technical, communication

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Master Data – How – Choose an architecture for this Master Data 7
Master Data App D
App E
Single version of truth
ConsumersProducers
 CENTRALIZATION / TRANSACTIONAL
 ADVANTAGES
 No duplicates
 Allows stewardship (workflow, DQ)
Entry point : master data database
 CONS
 Often, need consolidate at
first
 Need high availability (MDM
is the direct DB for
consumers)
 USAGES
 New data (ex : from Excel files)
 Need strong governance

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Master Data – How – Choose an architecture for this Master Data 8
 COOPERATION / CO-EXISTENCE
Master Data App D
App E
Single version of truth
ConsumersProducers /
Consumers
App C
App A
Entries points : business databases + master data database
 ADVANTAGES
 Cooperation vision
 Allows stewardship (workflow, DQ)
 CONS
 Duplicated MD
 Need to have MD up to date
 If producer needs back
loop, could be complex to
integrate
 USAGES
 Need flexibility governance
 Need uniformity between data
sources

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Master Data – How – Choose an architecture for this Master Data 9
 CONSOLIDATION
App A
App B
App C
Master Data App D
App E
Single version of truth
ConsumersProducers
Entries points : business databases
 ADVANTAGES
 Non intrusive
 Allows stewardship (workflow, DQ)
 CONS
 Duplicated MD
 USAGES
 Used to initialize MD database
 Few producers
 Need strong governance

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Master Data – How – Choose an architecture for this Master Data 10
 VIRTUAL / REGISTRY
App A
App B
App D
App E
App C
virtual repository
index
Consumers
Entry point : service of requests
 ADVANTAGES
 Non intrusive
 Low cost
 CONS
 No stewardship, no DQ
 Virtual master data
 USAGES
 No DQ needed
 No governance needed
 Need real time

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Master Data – How – Architecture synthesis 11
Usages Advantages Architecture
Centralized
Co-existence
Consolidation
Registry
Cons
Need strong governance
New Data (Excel)
No duplicate
Data Quality
Stewardship
Consolidation at first
MD database centric (high
availability)
Need flexibility
governance
Need uniformity
between data sources
Need to initialize MD DB
Need strong governance
Few producers
Need real time
No DQ needed
No governance needed
Cooperative vision
Data Quality
Stewardship
Non intrusive
Data Quality
Stewardship
Non intrusive
Low cost
Duplciated MD
Process to have MD up to
date
Back loop
Duplicated MD
No Data Quality
No Stewardship
Virtual MD

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Master Data - References 12
 REFERENCES
 https://www.semarchy.com/semarchy-blog/backtobasics-mdm-hub-patterns
 Book : Master Data Management in Practice: Achieving True Customer MDM
 Book : Master Data Management and Data Governance