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Master Data Management. Why Should a DBA Care?. Agenda. Master Data Management and the Data Base Professional Master Data Management Issues An approach to solving Master Data Management. Making Sense Of It All. Surrounding the DBA. So, what’s of interest to the Data Base Professional.

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master data management

Master Data Management

Why Should a DBA Care?

agenda
Agenda
  • Master Data Management and the Data Base Professional
  • Master Data Management Issues
  • An approach to solving Master Data Management
so what s of interest to the data base professional
So, what’s of interest to the Data Base Professional
  • Companies are looking for
    • Cost reduction initiatives
    • Revenue generation initiatives
    • Cross-sell opportunities
    • ROI in 12 months or less
  • The Data Base Professional has a unique view into
    • Data Structures
    • Data Quality
    • Metadata
    • Enterprise data assets, especially those spanning multiple departments
  • The Data Base Professional has the unique position of interfacing between
    • The Physical
    • The Logical
    • The Enterprise
agenda7
Agenda
  • Master Data Management and the Data Base Professional
  • Master Data Management Issues
  • An approach to solving Master Data Management
what is master data management

Master Data

Management

System

New

Applications

What is Master Data Management?

MasterData

Existing

Applications

  • Decouples master information from individual applications
  • Becomes a central, application independent resource
  • Simplifies ongoing integration tasks and new app development
  • Ensure consistent master information across transactional and analytical systems
  • Addresses key issues such as data quality and consistency proactively rather than “after the fact” in the data warehouse

Existing

Applications

MasterData

Existing

Applications

Historical /AnalyticalSystems

MasterData

master data management 101 strategic view

… to serve customers

What

Who

… by delivering products and services to them

Product

(SKU, Bundle,

Part, Service, Assets)

Party

(Individual and Org Customer, Employee, Supplier, Partner, Citizen)

… via effective understanding of their relationship with them

Account

(Financial account, loyalty points, agreement, contract)

How

Master Data Management 101:Strategic View
  • Enterprises exist …

Location

  • Primary Domains
  • Product
  • Party
  • Account
  • Supporting Domains
  • Location
mdm builds on infrastructure and provides context

Business

Business Object in the Context of Other Objects

Business Object with Interface Exposed as Services: Behavior

Product

Customer Specific Pricing

  • checkCredit()
  • fetchAddressHistory()
  • mergeAccounts()

Value Proposition

Standalone Business Object

RDBMS, XML Repositories, Unstructured Content Rep.

Customer

Customer

Customer

Infrastructure

MDM Builds on Infrastructure and Provides Context
slide11

Web Site

Contact Center

Enterprise Systems

Data Warehouse

Business

Processes

Business

Processes

Business

Processes

Business

Processes

Operational

Functions

Operational

Functions

Operational

Functions

Operational

Functions

Root Cause

Collaboration

Collaboration

Collaboration

Collaboration

Analytics

Analytics

Analytics

Analytics

Customer

Customer

Customer

Customer / Shipping

Customer / Shipping

Product

Product

Product

Product

Location

Location

Location

Location

Symptom

Supplier

Supplier

Account

Order

Order

Order

Order

Analytic / Insight

Analytic / Insight

Analytic / Insight

Analytic / Insight

The key word in Master Data Management isn’t “Data” … it’s ”Management”

  • Many organizations attempted to address only the symptoms and have used:
      • Data cleansing tools
      • Data integration tools
      • Data-centric MDM
    • The result? They didn’t solve the problem, data is still out-of-synch, and they have one more siloed repository
  • In order to solve the problem completely, address the root cause – the functionality that manages the data
    • Collaboration – Data definition, creation, and synchronization with all consumers of data
    • Operations – SOA data management functionality
    • Analytics – Generate insight on master data

Don’t confuse the symptoms with the root cause

Other MDM vendors focus on the symptom (the data) and deliver data-centric tools. IBM is the only vendor who delivers Multiform MDM addressing the Management of master data for all uses and all domains.

slide12

Symptom - Islands of key business data = no master dataSlow time to market for products,poor customer satisfaction,missed revenue opportunities

  • Today most companies have multiple repositories for key business data like customers, products, suppliers, locations, and accounts
  • This results in:
    • Inability to understand the value of the customer
    • Inconsistency in product data across systems
    • Missed revenue opportunity due to slow product introduction process
    • Inconsistent customer service across channels

Web Site

Contact Center

Enterprise Systems

Data Warehouse

Customer

Customer

Customer

Customer / Shipping

Customer / Shipping

Product

Product

Product

Product

Location

Location

Location

Location

Supplier

Supplier

Account

Order

Order

Order

Order

symptom a distortion of reality siloed data does not accurately represent key business facts

A Customer …

Name: Jane Smith

Address: 123 Oak

Account #: 44444

Transaction: purchased

a gas grill

A Product …

Name: Gas Grill

SKU: 1111111

Current Price: $550

A Location …

Store #: 555

Symptom - A Distortion of realitySiloed data does not accurately represent key business facts

Key Business Information

Current Representation of Key Business Facts

Web Site

Contact Center

Enterprise Systems

Data Warehouse

Jane Smith

J. Smith

Jane Smith-Brown

123 Oak Street

Ship to: 123 Oak

Gas Grill $550

Gas Grill $700

Prop. Grill $550

Propane Grill

Store 555

Oakmill Store

Store 555

Store 555

Grills Inc.

Big Grill Corp.

Account

Purchased Gas Grill

Purchased Tongs

Purchased Gas

Purchased Gas Grill

Applications force you to manage data in silos and are not capable of accurately representing the key facts you need to run your business. Master Data Management is designed to manage a complete and accurate profile of all key data and provide each application with the appropriate profile.

slide14

“77% of 144 CIOs surveyed identified single view of customer as

the single most important benefit of MDM”

Symptom - A deeper look at the customer data problemReduce customer satisfaction, decrease revenue, hinder relationships
  • Is a high value web customer

Web Site

Contact Center

Data Warehouse

  • Companies quantify impact of bad customer data:
  • 66% indicate profitability of company as a whole was negatively affected by poor information quality
  • 75% indicate bad customer data quality is harming customer service, quality and loyalty
  • 52% identified integration of diverse systems as a major source of inaccurate information
  • Industry Drivers: Privacy Management, Basel II, “Do not Call” compliance, Patriot Act, Sarbanes Oxley, HIPAA

Name: Jane F. Smith

  • Yet… to the call center she is completely unknown
    • Poor customer service
    • High cost of service due to “multi call resolution”

Name: Jane Smith

Name:

Name: Jane F. Smith

Address:

Address: 123 Main St

Address: 437 Easy St

Cross-sell/Upsell Items:

5432, 4355

Preferences:

Preferences:

Sales History:

Products 5748, 6574

Sales History:

Products 1234, 5748

  • Inability to act on customer insight leads to missed sales opportunities

Account:

Customer Value: HIGH

Customer Value:

Customer Value: HIGH

slide15
Product SKU 11111

Product short description: Outdoor gas grill

Symptom - A deeper look at the product data problemInconsistent Shopping Experience due to inconsistent data across channels.

Web Site

Contact Center

Store

  • Gaining control over product information results:
  • Errors in data – 30% of data in retailers systems is wrong
  • Lost productivity – 25 minutes manual cleansing per SKU, per year
  • Slow time to market – 4 weeks to introduce new products
  • Invoice deductions – 43% of invoices result in deductions
  • Failed scans – up to 70,000 per week (1 large US Retailer)
  • Lost sales – up to 3.5% per year
  • Source: A.T. Kearney, GMA, AMR
  • Industry Drivers: RFID, Waste Electrical and Electronic Equipment Recycling, Product Information Exchange Standards, Return of Hazardous Substances, Global Data Synchronization, Sarbanes Oxley, etc. (Yankee Group, 2005)

Outdoor Gas Grill

Name: Jane F. Smith

Name: Jane F. Smith

Product: Outdoor grill

Product: Gas Grill

Product:

Price: $550 *Special

Price:

Price: $550 *Special*

Product: Gas Grill

  • Features: auto-shut off, rubber wheels, rotisserie, sound system
  • Price: Regular $700
  • Price: Sale $550 Expiry Sep. 30
  • Warranty 1 year
  • Return Policy 30 days

Cross-sell/Upsell Items:

5432, 4355

Cross-sell/Upsell Items:

Price: $700

Warranty: 1-year

Warranty:

Warranty: 1-year

Features:

Features: Auto shut-off,

Rubber wheels, rotisserie

Features: Sound system,

Rotisserie

Warranty: 1-year

Stock:

Features: sound system, rotisserie

Return Policy: 30 days

Return Policy: 30 days

Return Policy:

Return Policy: 30 days

Return Policy: 30 days

“79% of Retailers and 61% of CPG manufacturers rank

“item management” as their top priority”

root cause current systems are a barrier

Business

Processes

Business

Processes

Business

Processes

Business

Processes

Operational

Functions

Operational

Functions

Operational

Functions

Operational

Functions

Collaboration

Collaboration

Collaboration

Collaboration

Analytics

Analytics

Analytics

Analytics

“Through 2010, fewer than 20 percent of large organizations will satisfy their single view of the customer requirement solely by using the data model and database beneath a vendors application suite.”

Root Cause – Current systems are a barrier

The “Master” Data Challenge

Web Site

Contact Center

Enterprise Systems

Data Warehouse

  • Which one is (or could be) the master for all key business data items?
  • Unfortunately, none of them can
  • They are all consumers (users) of data … they are not managers of that data
    • Different definitions of data
    • Different usage requirements for data
    • Only care about data from the narrow POV of their application business process

Customer

Customer

Customer

Customer / Shipping

Customer / Shipping

Product

Product

Product

Product

Location

Location

Location

Location

Supplier

Supplier

Account

Order

Order

Order

Order

Analytic / Insight

Analytic / Insight

Analytic / Insight

Analytic / Insight

root cause current applications have caused the master data problem
Root Cause – Current Applications have caused the master data problem

Fragmented and incomplete data management functionality is the root cause of the master data problem

Web Site

Contact Center

Enterprise Systems

Business

Processes

Business

Processes

Business

Processes

  • Each system has discrete and often contradictory functionality to manage data
    • Business processes – any process related to data management and is reusable across applications
    • Operational – functions for providing data to operational processes
    • Collaboration – functions to define, collaborate, and manage master data definition & creation
    • Analytics – functions to generate insight into data
  • Lack of consistency across the enterprise for master data functions is the root cause of the master data problem

Operational

Functions

Operational

Functions

Operational

Functions

Collaboration

Collaboration

Collaboration

Analytics

Analytics

Analytics

Customer

Customer

Customer

Customer / Shipping

Customer / Shipping

Product

Product

Product

Location

Location

Location

Supplier

Supplier

Account

Order

Order

Order

slide18
Data is used by many applications, each for different reasons
    • That means that each application
      • Requires a unique set of data
      • Requires a unique set of functions to create and use that data
      • Requires different analysis of that data
  • The data lifecycle recognizes key facts
    • Data is dynamic
    • Data needs to be created, used, and analyzed in a variety of ways by data consumers
    • Data management requires its own lifecycle management – creation, usage, analysis, event detection, refresh schedule, subscription management – are all data-centric processes

Root Cause - Understanding the data lifecycleApplication business processes arethe trigger for data creation, usage,and analysis – but their “siloed”functionality doesn’t address each others requirements

root cause understanding the data lifecycle

Business

Processes

Business

Processes

Operational

Functions

Operational

Functions

Collaboration

Collaboration

Analytics

Analytics

Root Cause – Understanding the data lifecycle

Application business processesare the trigger for data creation,usage, and analysis – but theirsiloed functionality doesn’t addresseach others requirements

Web Site

Contact Center

Enterprise Systems

Business

Processes

  • Product A is defined in the Enterprise system

Operational

Functions

Collaboration

Analytics

Product

Supplier

root cause understanding the data lifecycle20

Business

Processes

Operational

Functions

Collaboration

Analytics

Root Cause – Understanding the data lifecycle

Application business processesare the trigger for data creation,usage, and analysis – but theirsiloed functionality doesn’t addresseach others requirements

Web Site

Contact Center

Enterprise Systems

Business

Processes

Business

Processes

  • Product A is defined in the Enterprise system
  • Enterprise product data is synchronized to the web store
    • Different definitions of data results in errors

Operational

Functions

Operational

Functions

Collaboration

Collaboration

Analytics

Analytics

X

Product

Product

Supplier

Supplier

root cause understanding the data lifecycle21

Business

Processes

Operational

Functions

Collaboration

Analytics

Root Cause – Understanding the data lifecycle

Application business processesare the trigger for data creation,usage, and analysis – but theirsiloed functionality doesn’t addresseach others requirements

Web Site

Contact Center

Enterprise Systems

Business

Processes

Business

Processes

  • Product A is defined in the Enterprise system
  • Enterprise product data is synchronized to the web store
    • Different definitions of data results in errors
  • A customer orders that product on the web store
    • Doesn’t identify the customer as a prior client
    • Web store captures a portion of the customer profile – first and last name, address, email address
    • Enterprise system processes to order and captures the client data only as a “ship to” address

Operational

Functions

Operational

Functions

Collaboration

Collaboration

Analytics

Analytics

?

Customer

Customer / Shipping

Customer / Shipping

Product

Product

Location

Supplier

Supplier

Account

Order

Order

root cause understanding the data lifecycle22
Root Cause – Understanding the data lifecycle

Application business processesare the trigger for data creation,usage, and analysis – but theirsiloed functionality doesn’t addresseach others requirements

Web Site

Contact Center

Enterprise Systems

Business

Processes

Business

Processes

Business

Processes

  • Product A is defined in the Enterprise system
  • Enterprise product data is synchronized to the web store
    • Different definitions of data results in errors
  • A customer orders that product on the web store
    • Doesn’t identify the customer as a prior client
    • Web store captures a portion of the customer profile – first and last name, address, email address
    • Enterprise system processes to order and captures the client data only as a “ship to” address
  • Product B is discounted in the Enterprise system
    • Change is not reflected in the contact center because the Enterprise system doesn’t understand who subscribes to that change

Operational

Functions

Operational

Functions

Operational

Functions

Collaboration

Collaboration

Collaboration

Analytics

Analytics

Analytics

Customer

Customer / Shipping

Customer / Shipping

$

$

$

Product

Product

Product

Location

Location

Supplier

Supplier

Account

Order

Order

root cause understanding the data lifecycle23
Root Cause – Understanding the data lifecycle

Application business processesare the trigger for data creation,usage, and analysis – but theirsiloed functionality doesn’t addresseach others requirements

Web Site

Contact Center

Enterprise Systems

Business

Processes

Business

Processes

Business

Processes

  • Product A is defined in the Enterprise system
  • Enterprise product data is synchronized to the web store
    • Different definitions of data results in errors
  • A customer orders that product on the web store
    • Doesn’t identify the customer as a prior client
    • Web store captures a portion of the customer profile – first and last name, address, email address
    • Enterprise system processes to order and captures the client data only as a “ship to” address
  • Product B is discounted in the Enterprise system
    • Change is not reflected in the contact center because the Enterprise system doesn’t understand who subscribes to that change
  • Customer orders product B via the call center
    • Doesn’t get the correct discount
    • Call center captures a different customer profile – name, phone number, address

Operational

Functions

Operational

Functions

Operational

Functions

Collaboration

Collaboration

Collaboration

Analytics

Analytics

Analytics

Customer

Customer

Customer / Shipping

Customer / Shipping

Customer / Shipping

$

Product

Product

Product

Location

Location

Location

Supplier

Supplier

Account

Order

Order

Order

root cause the end result the majority of data is incorrect

Business

Processes

Business

Processes

Business

Processes

Operational

Functions

Operational

Functions

Operational

Functions

Collaboration

Collaboration

Collaboration

Analytics

Analytics

Analytics

Root Cause – The end result, the majority of data is incorrect

These are the key facts aboutyour business that directlyimpact your success

Web Site

Contact Center

Enterprise Systems

  • Very quickly, data will become
    • Out-of-synch
    • Incomplete
    • Inaccurate
  • The root cause is separate application functionality for data-centric functionality
  • How many transactions does your organization process each day?
  • If the root cause is the application function itself, how can you keep up with the pace of enterprise data corruption

Customer

Customer

Customer / Shipping

Customer / Shipping

Product

Product

Product

Location

Location

Location

Supplier

Supplier

Account

Order

Order

Order

slide25

Business

Processes

Business

Processes

Business

Processes

Operational

Functions

Operational

Functions

Operational

Functions

Collaboration

Collaboration

Collaboration

Analytics

Analytics

Analytics

  • Master data is treated as a data model and low-level data access functionality
    • “A common data model will solve your data problems”
  • Key master data management functionalityremains in the consuming applications(their application suite)
  • End result = data problems will continue and you will have “one more incorrect database”

Web Site

Contact Center

Enterprise Systems

Application Centric ViewApplication may notseparate master data functionfrom application function

Master Data Management in Application Suite

Limited Data Integration Capabilities

Conclusion:

”Data Consumers don’t make good data managers”

slide26

Business

Processes

Business

Processes

Business

Processes

Operational

Functions

Operational

Functions

Operational

Functions

Collaboration

Collaboration

Collaboration

Analytics

Analytics

Analytics

Niche Solution – Master Data Management from single-faceted perspectiveNiche solution often address onlyone usage pattern or domain,

  • Niche solution typically focus on only one domain and one usage scenario
  • But your requirements are for multi-dimensional usage of data across multiple domains
  • You end up starting with the vendor’s domain, then realize you can’t build upon what you have
  • Most of these vendors offer very limited integration functions – they attempt to integrate data but are not robust enough to perform

Web Site

Contact Center

Enterprise Systems

Analytical

Product

Operational

Location

Collaborative

Customer

Product

Customer

Customer

Limited

Data Integration

Limited

Data Integration

Limited

Data Integration

Conclusion:

”You can’t get there from here with niche solution, it may not have the breadth of MDM functionality”

slide27

As most data sources are also consumers the integration of data and applications is challenging.

Keeping Data Integration in the picture

Your infrastructure looks like this …

…but data integration complexity is downplayed

Integration is about more than having a set of staging tables or a message queue adapter

agenda28
Agenda
  • Master Data Management and the Data Base Professional
  • Master Data Management Issues
  • An approach to solving Master Data Management
slide29

Customer

Customer / Shipping

Business

Processes

Business

Processes

Business

Processes

Business

Processes

Operational

Functions

Operational

Functions

Operational

Functions

Operational

Functions

Location

Collaboration

Collaboration

Collaboration

Collaboration

IBM Master Data Management

Customer

Customer

Customer

Industry SOA Business Processes

Analytics

Analytics

Analytics

Analytics

Customer / Shipping

Customer / Shipping

Product

Product

Product

Product

Location

Location

Location

Collaborative MDM

Operational MDM

Analytical MDM

Supplier

Supplier

Account

Order

Order

Order

Order

Analytic / Insight

Analytic / Insight

Analytic / Insight

Analytic / Insight

Supplier

Product

Account

Location

Event Management

Data Quality Management

Data Lifecycle Mgmt

Web Site

Contact Center

Enterprise Systems

Data Warehouse

  • Separation of common data functionality into an enterprise application
  • Integration of data function via business services to serve all data consumers
  • Master data management is complementary to application processes
    • It provides applications with accurate and complete data about all key business entities

A Harmonized Solution approachSeparation of applicationfunction from data functionto create common dataprocessing capabilities

slide30
Understanding Data Managers v. Data ConsumersBuilding a system of checks and balances betweendata processes and application processes

Data consumers are not designed for data management – their data management functionality

is defined narrowly within the confines of the individual application.

a harmonized approach to master data management key characteristics
Multiform MDM

Multiple Styles

Collaborative MDM – Definition, creation, synchronization

Operational MDM – SOA management of master data

Analytical MDM – Analysis and insight

Multiple Domains

Support for multiple master data subject areas

Enterprise business processes - SOA industry models

Integrate master data with data consumers (business applications)

Customer

Customer / Shipping

Master Data Management

Industry SOA Business Processes

Collaborative MDM

Operational MDM

Analytical MDM

Supplier

Product

Account

Location

Event Management

Data Quality Management

Data Lifecycle Mgmt

A Harmonized Approach to Master Data ManagementKey Characteristics

Web Site

Contact Center

Enterprise Systems

Data Warehouse

slide32
Multi-Style

Collaborative MDM

Authoring, workflow, check in/out services to support collaboration on master data creation, management and quality control

Operational MDM

Business services to ingest master data from range of sources, manage it and fulfill all consumer uses of master data

Over 500 Business Services

Act as “System of Record”

Analytic MDM

Identity resolution & relationship discovery

Master data simplifies input to analytical environments (DWs) and improves quality (MDM is source)

Enterprise reporting and analytics

Industry-specific data warehouses

Multi-Domain

Support for Customer, Product, Account, Location, Supplier ….

Master Data ManagementCore Capabilities

  • Data Quality Management
    • Duplicate record processing
    • Data validation, cleansing & standardization
  • Event Management
    • Event detection & management
    • Notification to business processes and systems
  • Data Lifecycle Management
    • Data Governance
    • Data access management
    • Auditing, enterprise rules and policies
slide33

Master Data Management ApproachKey Technology Aspects

  • Service Oriented Architecture
  • Standards-based, Open
  • Application and Process

Neutrality

  • Domain-centrity/Multi-domain

capable

  • Multi-styles capable
  • Highest Performance and Scalability
  • Extensibility, while safeguarding upgradeability
  • Flexibility and Modular
  • Reactive and proactive
slide34

Customer

Customer / Shipping

Industry SOA Business Processes

Collaborative MDM

Operational MDM

Analytical MDM

Supplier

Product

Account

Location

Event Management

Data Quality Management

Data Lifecycle Mgmt

Master Data ManagementCollaborative MDM

  • Flexible, scalable repository managing and linking product, location, trading partner, organization, and terms of trade information
  • Tools for modeling, managing, capturing and creating this information with high user productivity and high information quality
  • Integrating and synchronizing this information internally with legacy systems, enterprise applications, repositories and masters
  • Workflow and solutions for supporting multi-department and multi-enterprise business processes
  • Exchanging and synchronizing this information externally with business partners
  • Leveraging this information via many internal and external electronic and human touch points
  • MDM Process Services
  • Initiate NPI Workflow
  • Check-out Item
  • Publish Catalog
slide35

Customer

Customer / Shipping

Industry SOA Business Processes

Collaborative MDM

Operational MDM

Analytical MDM

Supplier

Product

Account

Location

Event Management

Data Quality Management

Data Lifecycle Mgmt

Master Data ManagementOperational MDM

  • Build from the ground up as an SOA solution
  • Extensive range of business services (500+)
  • Designed for integration with operational applications
  • Contains both large and fine grain services
    • Add customer (large grain)
    • Update account
    • Get product
  • Flexibility
    • Easily extend or build new services from existing services
    • Fit product to meet the process, not vice-verse
  • Business services are “intelligent” containing packaged and configurable interfaces to business logic components
  • MDM Business Services
  • Add Customer
  • Open Account
  • View hierarchy
  • profile
master data management analytical mdm
Analytical MDM addresses the need to augment MDM operational services with “inline” decision support analytics for purposes of reducing risk of increased costs, regulatory or reputation damage such as through:

Compliance Adherence

Thread and Fraud Detection

Conflict Management

Note -- MDM integrates with traditional Analytics (Data Warehouses) as source of quality data to the DW and as consumer of DW information (e.g. lifetime value information)

Customer

Customer / Shipping

Industry SOA Business Processes

Collaborative MDM

Operational MDM

Analytical MDM

Supplier

Product

Account

Location

Event Management

Data Quality Management

Data Lifecycle Mgmt

Master Data ManagementAnalytical MDM
  • MDM “Inline” Analytics
  • Identify Thread/Fraud
  • Conflict of Interest
  • AML Alerts
slide37

X-Sell / Up-Sell Items: 5432, 4355

Master Data ManagementThe complete master data profile

  • The master data profile provides the current, accurate and complete business entity data to all systems and channels
  • Maintains detailed data on all key business entities
    • Customers & parties
    • Product
    • Account
    • Hierarchies
    • Location
    • Relationships

Master Data Services

Customer:

Jane Smith

Supplier:

Big Grill Co.

Product:

Gas Grill

Account

Cust. Ship-to

Location

Demographics:

Income - $100,000

Interests - Running

Age - 41

Relationships

Household

Daughter – Jenny

Husband – John

Employer – IBM

Address:

Home - 123 Main St

Billing – 437 Easy St

Privacy Preferences:

Solicitation - No

Life Events:

Daughters Birthday

Wedding Anniversary

Agreements & Contracts

Service Contract

Warranty

Sales History: Product 1234, 5748, 6574

Interaction History:

Service Issue 4/23/06

Web Order 2/2/06

Store Order 1/5/06

Identifier IDs

Customer Value: High

…..

…..

…..

mdm and data warehousing
MDM and Data Warehousing
  • Master Data Management (MDM) and Data Warehousing (DW) complement each other; they have significant synergies
    • MDM and DW provide quality data to the business but MDM is valuable beyond the DW for 2 reasons
      • Latency
      • Feedback

Analytic Services

(DW Models,

Identity Services & Predictive Analytics )

Data

Services

Metadata

  • MDM and DW have different use cases
    • MDM provides a “golden” source of truth that is used collaboratively for authoring, operationally in the transactional / operational environment and supports the delivery of "quality" Master Data to a DW system
    • DW systems are a multidimensional collection of historical transactional data that may be include than Master Data used to determine trends and create forecasts
    • Introducing MDM enhances the value of existing DWs by improving data integrity and closing the loop with transaction systems
mdm and your enterprise architecture

Access

Transport and Collaboration

Delivery

Web Browser

Portals

Web Services

Devices

Analysis &Discovery

EmbeddedAnalytics

Query, Search & Reporting

Mining

Metrics

Visualization

Identity

Analytics

Information Services

Master Data

&

InformationIntegration

Information

Integrity

Lifecycle

Management

Hierarchy &

Relationship Mgmt

Authoring

Master Data

Event Management

ETL

EAI

EII

Semantic

Reconciliation

Balance and

Controls

Data Services

Metadata Services

Content Services

Data Repositories

Unstructured

Analytical

Operational

Master Data

Metadata

Security and Privacy

Systems andInfrastructure

Systems Management & Administration

Network & Middleware

Hardware & Software

Data Sources

Content Mgmt

Applications

Others..

MDM and Your Enterprise Architecture

Master Data Management is a critical layer in an Information Architecture

  • Key differentiator – trust – IBM will be there, we’ve done it before – we have services, support, training to make this work!
  • Key message – MDM isn’t a standalone packaged application, it’s integrated with everything – you want to work with a vendor that understands integration infrastructure

Legend:

Master Data Management Services

Master Data Integration Services

Supports developing Information

Intensive Solutions