Businesses depend on reliable, consistent and correct data that can be managed effectively and shared through-out the enterprise. Master Data Services provides a powerful, feature-rich platform for arriving at this destination but the successful journey to this end requires a proven integrated approach. This session will discuss how MDS fits in the overall EIM architecture within your organization including real-world strategies for integrating (cleansing, matching and loading) Master Data into MDS and for making it available organization-wide.

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Chris Price
Senior BI Consultant
@BluewaterSQL
MDS: An Integrated Approach

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Intro
Chris Price
Senior BI Consultant with Pragmatic Works
@BluewaterSQL
http://bluewatersql.wordpress.com/
cprice@pragmaticworks.com

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Today’s Agenda
• MDM Overview
• What is Master Data Services?
• Integration Options
– Data Warehouse
– Line of Business

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Master Data Management (MDM)
• Master Data Defined
– The building blocks of your business transactions
or the dimensions which describe facts in the DW
– Customers, Products, Employees, Locations, Etc.
– Data that is usually created, shared and
maintained across multiple applications
– Does not include transactional data (i.e. Sales)

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Master Data Management (MDM)
• Book Definition
– A set of tools, policies, procedures and services to provide
a single consistent view of uniquely identifiable of master
data
• Data Governance
– Defines ownership, access, change management, quality,
disaster recovery and retention
• Data Stewardship
– Appointed by the data governance board, generally one
steward per entity, often the subject matter expert,
responsible for the master data on a continuing basis

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The Master Data Challenge
MARKETING SERVICESHIPPINGSALES
CustomerProspectLeadCustomer
Product/Service/Pricing
OrderQuote
CRM ERP
Mktg Apps E-Commerce Site Call Center
DATA
SYSTEMS

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MDM in Business Intelligence
• Primarily focused on dimensional data
• Most DW implementations have already
attempted to enforce data manage master data
– Repairing data after transactions occur does not
improve data quality, need to push upstream
• Push MDM to data experts (data stewards
/information workers)
• DW should be the recipient of master data not
the master of it (SoC/Specialization)

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MDM & BI: Value Proposition
• Bad data costs money
• Improve data quality upstream
• Reduces size, complexity, brittleness and
scope of your BI Implementation
• Authoritative Source of Data
• Easier to implement permissions, change
approval and auditing

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MDS Integration Options
• Master Data Services
– WCF/API (Real-Time)
– Subscription Views
– Staging Tables (Batch)

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MDS Parts & Pieces
• Loading Data
– stg.[Entity Name]_Leaf
• (Staging Table)
– stg.udp_[Entity Name]_Leaf
• (Procedure to Kick-Off Batch by Batch Name)
• Consuming Data
– mdm.[Subscription View Name]
• Leaf Members
• Hierarchies & Collections

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Traditionally Speaking…

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Integrating MDS

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Loading MDS
• Step 1: Cleanse & Validate
– DQS
• Step 2: Match
– Key Lookup
– Attribute Match (i.e. Email, SSN, etc.)
– Fuzzy
• Step 3: Load
– Stage
– Batch

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Sample MDS Load
Customer ID First Name Last Name Email
123456 Bill Gates bill@microsoft.com
Person ID Name Email
555489 Bill Gates bill@microsoft.com
User ID First Name Last Name Email
A98765 William Gates bill@microsoft.com
ERP
CRM
WEB
Customer Key First Name Last Name Email
999888777 Bill Gates bill@microsoft.com
Customer Key CustomerID System
999888777 123456 ERP
999888777 555489 CRM
999888777 A98765 WEB
Customer (Entity)
Customer Map (Entity)
Cleanse & Load

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Thank you!
Don’t forget to fill
out your evaluations!
@BluewaterSQL
http://bluewatersql.wordpress.com/
cprice@pragmaticworks.com