Informatica on
Master Data Management
October 2009
Michael Destein
Director, MDM Solutions Marketing
[email protected]
Wes Davis
District Manager
[email protected]
+1 (770) 510-2720
1
Agenda
• What is Master Data Management?
• What problem does it solve?
• What are the business drivers that justify MDM
investments?
• What are the technical requirements?
• What does Informatica do for MDM
2
Definition:
What is Master Data Management?
Gartner
Forrester
Wikipedia
Master data is the consistent and
uniform set of identifiers and extended
attributes that describe the core entities of
the enterprise — and are used across
multiple business processes.
Master data management (MDM) is a
business capability enabled through
the alignment of multiple information
management technologies, business
process improvements, and
organizational commitments.
Master data management (MDM)
comprises a set of processes and
tools that consistently defines and
manages the non-transactional data
entities of an organization (also called
reference data).
MDM is much more than a single
technology solution; it requires an
ecosystem of technologies to allow the
creation, management, and distribution
of high-quality master data throughout
the organization.
MDM has the objective of providing
processes for collecting,
aggregating, matching,
consolidating, quality-assuring,
persisting and distributing such
data throughout an organization to
ensure consistency and control in the
ongoing maintenance and application
use of this information.
Some examples of core entities are:
parties (customers, prospects, people,
citizens, employees, vendors, suppliers or
trading partners), places (locations, offices,
regional alignments or geographies) and
things (accounts, assets, policies, products
or services).
Groupings of master data include:
organizational hierarchies, sales territories,
product roll-ups, pricing lists, customer
segmentations, preferred suppliers and so
forth.
3
What does MDM look like to an
organization?
Hi, I would like to
open a new
account.
Sure. Do you
have any existing
accounts with us?
4
What does MDM look like to an
organization?
I’m not sure. You
guys have done
so many
mergers, it’s hard
for me to keep
up. My name is
Johann Graeme.
Ok, let me look it
up
5
What does MDM look like to an
organization?
Yohann Graham
John Graham – 22 Elm St.
John Graham – 8992 Meadow Lane
J T Graeme – 7 East 1st St., Suite 3
Yolanda Graham – 742 Maple Ave.
Graham Yocum – 992 Benson Way
I’m at number 7,
east first street
What is your
address?
6
What does MDM look like to an
organization?
Oh, I’ll send you
a check today.
J T Graeme
System
ID
Display Info
7 East 1st St
Suite 3
New York, NY
10003
CRM
3993
J T Graeme
Billing
9298
Johann Graeme
Credit Status:
$5 Past Due
Products Owned:
7- Widgets, 10 - Gadgets
Customer Since: 1984
OFFER: 2 for 1 Widgets
I’ve found your
records. You
have a past due
of $5, but we can
open a new
account
7
What does MDM look like to an
organization?
J T Graeme
System
ID
Display Info
7 East 1st St
Suite 3
New York, NY
10003
CRM
3993
J T Graeme
Billing
9298
Johann Graeme
Web
7292
J T Graeme
Credit Status:
$5 Past Due
I’d like to get the
web account
OFFER: 2 for 1 Widgets
Ok, you are all
set. Once we
receive the past
due amount, you
account will be
activated.
8
What does MDM look like to an
organization?
Oh, I forgot, I
need to change
my address to
628 East 57th
Street
New York City
J T Graeme
System
ID
Display Info
st thSt
7 East
628
E. 1
57
St
SuiteYork,
3
New
NY
New York, NY
10022
10050
CRM
3993
J T Graeme
Billing
9298
Johann Graeme
Web
7292
J T Graeme
Credit Status:
$5 Past Due
OFFER: 2 for 1 Widgets
No problem. I’ve
changed the
address for all of
your accounts
9
What does MDM look like to an
organization?
J T Graeme
System
ID
Display Info
st thSt
7 East
628
E. 1
57
St
SuiteYork,
3
New
NY
New York, NY
10022
10050
CRM
3993
J T Graeme
Relationship
Check:
Billing
9298 Johann Graeme
Web
7292
J T Graeme
Sally Graeme at same address
Credit Status:
Click Here to add to household
$5 Past Due
Yes, she is my
wife
OFFER: 2 for 1 Widgets
Oh, we have a
Sally Graeme at
that address.
10
What does MDM look like to an
organization?
Oh yes, next
week is her
birthday. Please
send them!
J T Graeme
System
ID
Display Info
st thSt
7 East
628
E. 1
57
St
SuiteYork,
3
New
NY
New York, NY
10022
10050
CRM
3993
J T Graeme
Billing
9298
Johann Graeme
Web
7292
J T Graeme
Credit Status:
$5 Past Due
OFFER: Dozen Roses and Birthday Vase
We have a
special offer of a
dozen birthday
roses….
11
Business Drivers for
Data Governance and Master Data Management
Mitigate
Risk & Fraud
Streamline
Operations

 Risk management
 Accurate books &
records
 Compliance with
AML & KYC
regulations
 Compliance with
corporate standards
and policies
 Avoid regulatory
fines and penalties
Improve Customer
Communications
*
 Provide accurate &
consistent customer
information through
all channels at all
touch points
 Reduce customer
acquisition and
account setup costs
 Streamline territory
management
 Identify and eliminate
 Reduce account
(
setup time and
remove incorrect &
duplicate data entry
 Improve customer
service wait time
 Provide consolidated
statements
 Single opt in – opt
out preferences
commission payment
overlap
Increase Revenue
& Marketing
Efficiency
$
 Increase cross sale
and up sale success
 Improve customer
loyalty, reduce
attrition/churn
 Reduce marketing
costs
 Solicit greater
campaign demand
 Create ―right‖
products for ―right‖
customers
 Increase sales
Business value drives requirements and pace of adoption:
Your architecture should support incremental value over time with a
long term view towards of the future enterprise data architecture
12
The High Level Requirements for MDM
Integration
Data
Quality
MDM Hub
Complete Platform for MDM
and Data Governance
13
What goes into a MDM Hub?
Reference Data
Hierarchies
Name, Address, etc
Cross References
Account 1
Account 2
Account n
14
MDM Hubs - Registry Style
CRM
Primary Key
First Name
Last Name
929992
John
Smith
ERP
Primary Key
AKK-111
 Matching Engine uses fuzzy logic to identify
common data entities.
 The
matchesLast
are done
First
Name
Nameon a subset of the attributes
for the master data entity (i.e. first and last name)
Johnson
Smith
Master Registry
Matching
Engine
 The Matching engine will create a unique ID and
Legacy
select the attributes from a contributing record to
Primary Key
Full
Namepurposes
use for
display
098388188
•
JohnSmith
The Matching engine will also create a cross
Unique ID
reference index storing the unique id, the
contributing source system and that systems111
Registries areprimary
goodkeys
for for the master data entity
de-duplication and identity resolution
• Used to search for account ids for a
particlar customer
• They don’t provide accuracy,
completeness, standardization, or
enrichment
First Name
Last Name
John
Smith
Unique
ID
Source
System
System ID
111
CRM
929992
111
ERP
AKK-111
111
Legacy
098388188
15
MDM Hubs – Co-Existence Style
CRM
ID
FName
LName
Status
Phone
Address
E-Mail
• Co-Existence Style MDM Hubs allow any system to
929992 John
Smith
Gold
650/555-1212
123 Elm, San Francisco CA 94044
[email protected]
create, update, or delete master data entities and
attributes.
ERP
duplicates,
inaccuracies,
incomplete, nonID
First Name • AnyLast
Name SSN
Address
Tax Status
to be applied Taxable
to
standard
arbitrated123
inData
the
hub
tofunctions
create
a94404-2356
AKK-111 Johnson
Smith data is
123-45-1234
ElmQuality
St,
San
Mateo,
CAneed
determine
 ―Golden
Like Registry
Style, the Co-existence
system which
also attribute from contributing
Record‖
Legacy
ID
098388188
Matching
Engine
Arbitration
Rules
source systems is to be the most trusted as well
matches records from multiple system
as standardizing the data, ensuring accuracy and
integrity,Phone
and potentially enriching
the data with
Full Name
Address
DOB
external data sources
J. A. Smith
121 Elm St. San Mateo CA 94404
4155551212
10/23/69
UID
Fname
LName
Address
Phone
111
Johnson
Smith are
123
Elm St, San
Mateo, CA 94404
 Once records
matched,
the Co-existence
MDM 650.555.1212
Hub will arbitrate the conflicts and missing data to
Unique Record”
Source
System ID
create a “Golden
ID
System
111
CRM
929992
111
ERP
AKK-111
111
Legacy
098388188
DOB
23/10/1969
16
MDM Data Model
One Size Does NOT Fit All
A key decision is whether to build a data model or purchase one
(sometimes in conjunction with an MDM packaged solution).
Source: http://www.databaseanswers.org/data_models
17
Hub Requirements:
Relationships and Hierarchies
Social Networks
Household
Spouse
Colleague
Knows
Spouse
Child 1
Colleague
Colleague
Colleague
Child 2
Colleague
Owns
Bill of Materials
Corporate Structure
Works
for
Product
Global
Parent
Subsidiary
Component 1
Component 2
Subsidiary
Produces
Division
Division
Division
Component 3
Division
Component 4
18
Challenge of Master
Data Management…
19
Diversity
20
Data
Types?
Usage
Styles?
Control? Owner ship?
Business
Value?
Scope?
21
How to Manage the Diversity….
22
WHY DO I NEED TO BE
FLEXIBLE?
23
50%
MDM Initiatives Will
Fail To Achieve
Desired Results
24
Breadth & Redundancy
65%
of Global 2000
organizations will deploy
two or more domainspecific, MDM supporting
technologies
Gartner Predicts
Organizations have
5.2
CDI solutions on
average.
Customer Data Integration
Phillip Russom, Oct 2008
Dec 2009
25
Scaling the Maturity Curve
Forrester MDM Maturity Model
26
Typical MDM Implementation Lifecycle
Profile and
Prioritize
• Quality
Profiling
• Establish
Data Quality
Metrics
• Establish
Business
Metrics
• Prioritize data
entities and
processes
Migrate Data
• Define MDM
Data Model
• Identify
Source Data
& Gaps
• Identify
Reference
Codes
• Transform and
Load (Batch &
Real-time)
Create Composite
Record
• Cleanse Data
• Define
Scorecard
• Define
matching rules
• Merge records
• Relate master
data entities
Provision Master
Data
• Capture Data
Changes
• Create Data
Services
• Synchronize
using proper
modality
• Orchestrate
data
management
processes
Data Governance Principles
Expand to include
more source and target systems,
data entities, and data attributes
27
The key to successfully scaling
the MDM maturity curve is to
build a foundation of:
• Integration
• Data Quality
• Identity Resolution
28
Data Integration:
The cornerstone of MDM
29
Data Integration Requirements
• Accessing data inside
and outside the firewall
• Bi-directional
transformation
• Multiple latencies
• Process orchestration
• Data Federation
This is not your
father’s ETL!
• Metadata visibility
It’s a sophisticated
data integration platform
30
Why is data quality
so important?
31
It’s the
master data!
You are going to use it
everywhere
It’s your trusted source of truth
You will make decisions using it
32
Ensuring Data Quality
for Master Data
• You can’t fix it just once
•
You need to monitor and manage it as a process
• It’s not just Address Correction
•
It’s accuracy, consistency, completeness, enrichment,
matching and validation
• You need to know the source of the problems
• You won’t be successful just writing a few scripts
33
Matching
Identities
34
Why are customer data
integration projects
challenging?
• Identity data is subject to
considerable error and
variation
• Databases about people &
organisations often contain
international data
• Basic search techniques
frequently miss matches or
find too many matches
• Data cleansing is not the
complete answer
EXAMPLES
• Mary Anne, Maryanne
• Easthartford, Hartford East,
Hartford
• Browne – Brown
• Johnson, Jhonson
• Hannah, Hamah
• IBM/International Business
Machines
• Fedex/Federal Express
• Chris – Christine, Christopher,
Tina
35
MDM Requires a Hybrid
Approach to Identity
Matching
Deterministic
Heuristic
Empirical
Probabilistic
Phonetic
Linguistic
A combination of methods and algorithms will compensate for
different classes of error and variation present in identity data.
36
WHY INFORMATICA?
37
Informatica:
The Flexible Foundation for MDM
All Master Data Domains
Customers
Assets
Products
Suppliers
Locations
Employees
Data
Warehouse
All Purchase Models
All Hub Styles
Analytical
Co-existence
Registry
Transactional
Applications
Documents
Buy
Packaged
MDM
Build
Your
Own
SaaS
38
Unified Architecture
Orchestration | Human Workflow | Web Services
MDM Data Sources
Customer Facing
Applications
Identity Resolution
Data Modeling
Data Access
|
Data Latency
Master Data Hub
Master Record Composition
Campaign
Management
Customer
Portal
Data Publishing |
Data Steward Interface
Data Delivery
Cleanse & Transform
|
Data Synchronization
Data Profiling
eCommerce
Other
Applications
Hierarchy Management
Role Based Security
Upstream
Applications
Downstream
Applications
Metadata Management | Data Lineage | “Where Used” Analysis
39
Using Informatica for Master Data Management
MDM
Hub
Flat File
Database
•
PowerCenter drives initial loading of MDM Hub
•
Informatica Data Quality will cleanse and monitor the quality of
the data
•
Informatica Identity Resolution matches and links common
entities under a global ID
•
PowerCenter supports on-going updates and distributes master data
in any latency: batch, message based, real-time
40
The Informatica Platform
The MDM Foundation For These Customers
Build
Your Own
Build Your
Own
Oracle MDM
Siperian
MDM
Data
Warehouse
Initiate
Systems
SAP MDM
41
Next steps…
Start with a small
MDM Project now
and lay a foundation
of data integration,
data quality, and
identity resolution
A good place to
start is with a
Customer Registry
42
THANK YOU
43