Sample ORS Configuration Guide Informatica MDM Multidomain Edition for Oracle (Version 9.5.0)

Informatica MDM Multidomain Edition for Oracle
(Version 9.5.0)
Sample ORS Configuration Guide
Informatica MDM Multidomain Edition for Oracle Sample ORS Configuration Guide
Version 9.5.0
June 2012
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Table of Contents
Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
Learning About Informatica MDM Hub. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
Informatica Resources. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
Informatica Customer Portal. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
Informatica Documentation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
Informatica Web Site. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
Informatica How-To Library. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
Informatica Knowledge Base. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
Informatica Multimedia Knowledge Base. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
Informatica Global Customer Support. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi
Chapter 1: Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Chapter 2: Data Source Configuration. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Source Systems. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Data Origin by Source System. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Chapter 3: Data Model and Schema Configuration. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Overview of Data Model and Schema Configuration. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Data Model Entity-Relationship diagram. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Base Objects. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Landing Tables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Staging Tables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Chapter 4: Data Cleansing Configuration. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Source System Cleanse Maps. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Cleanse Functions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Chapter 5: Match and Merge Configuration. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Trust Settings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Trust Validation Rules. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
Match Rule Configuration. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Match Columns & Rules for Party Base Object. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Address Match Columns & Rules. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
Party Group Match Columns & Rules. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
Table of Contents
i
Chapter 6: Hierarchy Manager (HM) Configuration. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
Entity Objects and Types. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
Hierarchies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
Relationship Objects and Types. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
Hierarchy Manger Console. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
ii
Table of Contents
Preface
Welcome to the Sample ORS Configuration Guide. This guide provides an introduction to the ORS configuration
used by the Informatica MDM Hub sample applications included as part of the Resource Kit. This guide has been
written for application developers, database administrators, system administrators, and other technical members
of an MDM implementation team. For instructions on how to install the ORS and the Informatica MDM sample
applications, please refer to the Informatica MDM Hub Resource Kit Guide.
Learning About Informatica MDM Hub
What’s New in Informatica MDM Hub
What’s New in Informatica MDM Hub describes the new features in this Informatica MDM Hub release.
Informatica MDM Hub Release Notes
The Informatica MDM Hub Release Notes contain important information about this Informatica MDM Hub release.
Installers should read the Informatica MDM Hub Release Notes before installing Informatica MDM Hub.
Informatica MDM Hub Overview
The Informatica MDM Hub Overview introduces Informatica MDM Hub, describes the product architecture, and
explains core concepts that users need to understand before using the product. All users should read the
Informatica MDM Hub Overview first.
Informatica MDM Hub Installation Guide
The Informatica MDM Hub Installation Guide explains to installers how to set up Informatica MDM Hub, the Hub
Store, Cleanse Match Servers, and other components. There is an Informatica MDM Hub Installation Guide for
each supported platform.
Informatica MDM Hub Upgrade Guide
The Informatica MDM Hub Upgrade Guide explains to installers how to upgrade a previous Informatica MDM Hub
version to the most recent version.
iii
Informatica MDM Hub Cleanse Adapter Guide
The Informatica MDM Hub Cleanse Adapter Guide explains to installers how to configure Informatica MDM Hub to
use the supported adapters and cleanse engines.
Informatica MDM Hub Data Steward Guide
The Informatica MDM Hub Data Steward Guide explains to data stewards how to use Informatica Hub tools to
consolidate and manage their organization's data. Data stewards should read the Informatica MDM Hub Data
Steward Guide after having read the Informatica MDM Hub Overview.
Informatica MDM Hub Configuration Guide
The Informatica MDM Hub Configuration Guide explains to administrators how to use Informatica MDM Hub tools
to build their organization’s data model, configure and execute Informatica MDM Hub data management
processes, set up security, provide for external application access to Informatica MDM Hub services, and other
customization tasks. Administrators should read the Informatica MDM Hub Configuration Guide after having read
the Informatica MDM Hub Overview.
Informatica MDM Hub Services Integration Framework Guide
The Informatica MDM Hub Services Integration Framework Guide explains to developers how to use the
Informatica MDM Hub Services Integration Framework (SIF) to integrate Informatica Hub functionality with their
applications, and how to create applications using the data provided by Informatica MDM Hub. SIF allows
developers to integrate Informatica MDM Hub smoothly with their organization's applications. Developers should
read the Informatica MDM Hub Services Integration Framework Guide after having read the Informatica MDM Hub
Overview.
Informatica MDM Hub Metadata Manager Guide
The Informatica MDM Hub Metadata Manager Guide explains how to use the Informatica MDM Hub Metadata
Manager tool to validate their organization’s metadata, promote changes between repositories, import objects into
repositories, export repositories, and related tasks.
Informatica MDM Hub Resource Kit Guide
The Informatica MDM Hub Resource Kit Guide explains how to install and use the Informatica Hub Resource Kit,
which is a set of utilities, examples, and libraries that assist developers with integrating the Informatica Hub into
their applications and workflows. This document also provides a description of the various sample applications that
are included with the Resource Kit.
Informatica Training and Materials
Informatica provides live, instructor-based training to help professionals become proficient users as quickly as
possible. From initial installation onward, a dedicated team of qualified trainers ensure that an organization’s staff
is equipped to take advantage of this powerful platform. To inquire about training classes or to find out where and
when the next training session is offered, please visit Informatica’s web site (http://www.informatica.com) or
contact Informatica directly.
iv
Preface
Informatica Resources
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Informatica Documentation
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questions, comments, or ideas about this documentation, contact the Informatica Documentation team through
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know if we can contact you regarding your comments.
The Documentation team updates documentation as needed. To get the latest documentation for your product,
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Informatica Web Site
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about Informatica, its background, upcoming events, and sales offices. You will also find product and partner
information. The services area of the site includes important information about technical support, training and
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Informatica How-To Library
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The How-To Library is a collection of resources to help you learn more about Informatica products and features. It
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behaviors, and guide you through performing specific real-world tasks.
Informatica Knowledge Base
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Use the Knowledge Base to search for documented solutions to known technical issues about Informatica
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Informatica Multimedia Knowledge Base
As an Informatica customer, you can access the Informatica Multimedia Knowledge Base at
http://mysupport.informatica.com. The Multimedia Knowledge Base is a collection of instructional multimedia files
that help you learn about common concepts and guide you through performing specific tasks. If you have
questions, comments, or ideas about the Multimedia Knowledge Base, contact the Informatica Knowledge Base
team through email at KB_Feedback@informatica.com.
Preface
v
Informatica Global Customer Support
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vi
Preface
CHAPTER 1
Introduction
This chapter includes the following topic:
¨ Overview, 1
Overview
The following configuration areas of a Informatica MDM Hub implementation are described in this guide:
¨ Data source configuration
- Source systems
- Data origin by source system
¨ Data model and schema configuration
- Data model entity-relationship diagram
- Base objects
- Landing tables
- Stage tables
¨ Data cleansing configuration
- Source system cleanse maps
- Cleanse functions
¨ Match and merge configuration
- Trust settings
- Trust validation rules
- Match rule configuration with match examples
¨ Hierarchy Manager configuration
- Entity objects and types
- Hierarchies
- Relationship objects and types
1
The following Informatica MDM Hub Resource Kit applications rely on the sample ORS and configuration. For
more information on these applications, refer to the documentation in the Resource Kit sample folder for the
application.
¨ Informatica Data Director demo application
- Customer and product Master Data Management
- Informatica MDM workflow example
- Organization, household and product Hierarchy Management
¨ Business Process Management integration with Lombardi Teamworks
- Integration with SIF APIs using SOAP
- Integration with composite services using EJBs
¨ SIF SDK usage and SOA enablement (Web Service examples)
- Composite services creation from SIF APIs
- Lookup code management services
- Cross-reference services
2
Chapter 1: Introduction
CHAPTER 2
Data Source Configuration
This chapter includes the following topics:
¨ Source Systems, 3
¨ Data Origin by Source System, 3
Source Systems
This sample implementation of the Informatica MDM Hub integrates three primary source applications, one data
augmentation source, and a reference system. These sources provide the data for Party, Address, Household, and
Product information.
The primary data sources are:
SFA
A Sales Force Automation system providing party, address, household and account data.
Legacy
A legacy system providing party, address, household and relationship data
Product
A PIM system providing product and product relationship data.
The augmentation data source is:
Org Data Inc
Org Data Inc (ODI) source for additional party relationship and organization data.
The reference system is:
Lookups
A source system providing reference table data for lookups.
Data Origin by Source System
The data from the five source systems are associated with each system as follows:
3
SFA
Party
Address
Account
Electronic Address
Party Phone
Household
Party Group relationship
Party to Product relationship
Legacy
Party
Shipping Address
Billing Address
Household
Household to Party relationship
Product
Product
Product relationship
Product to Product relationship
ODI
Party
Address
Party Phone
Party Organization detail
Party Hierarchy data
Lookup
Type codes for Product, Address and Electronic Address
Lookup codes for Country, State, Gender, etc.
4
Chapter 2: Data Source Configuration
CHAPTER 3
Data Model and Schema
Configuration
This chapter includes the following topics:
¨ Overview of Data Model and Schema Configuration, 5
¨ Data Model Entity-Relationship diagram, 5
¨ Base Objects, 6
¨ Landing Tables, 11
¨ Staging Tables, 12
Overview of Data Model and Schema Configuration
This section describes the data model for the sample implementation, and defines the base objects, landing
tables, and staging tables that make up the sample ORS.
Data Model Entity-Relationship diagram
A Party data model has been defined to address the Master Data needs for Individual, Organization, and their
relationship to Account data. The data model also contains a Product data model to address product Master Data.
5
The following diagram, generated by the Informatica MDM Schema Viewer, depicts the data model configured in
the sample ORS.
Base Objects
The following tables describe the base objects that are defined in the Informatica MDM sample ORS:
Party Data Model Base Objects
Display Name
Table Name
Description
Account
C_ACCOUNT
Accounts held by a Party. Includes
credit cards, debit cards, store
accounts, and so on.
Address
C_ADDRESS
Consolidated addresses per customer.
Organization Details
C_ORGANIZATION_DETAILS
Enrichment data for organizations. The
core data is held on the Party base
object. The data on this child object are
less likely to need to be merged than
the data on the Party base object-and
keeping the details separate helps with
performance.
Data may come from 3rd party systems
(such as ODI)
Organization Standard Industry Code
6
Chapter 3: Data Model and Schema Configuration
C_ORGANIZATION_SIC
The Standard Industrial Classification
(abbreviated SIC) is a United States
government system for classifying
industries by a four-digit code.
Party Data Model Base Objects
Display Name
Table Name
Description
Party
C_PARTY
Party base object with Individual and
Organization data:
Tax Id
Can be organizations Tax Id or
Individuals Social Security
Number
Status Cd
Used to support workflow
(Pending, Active, or Deleted
state)
ODI Level
Determined by a Cleanse
Function within the schema
based on the data from ODI.
Display Name
The name to be shown on UI.
Party Account Relationship
C_REL_PARTY_ACCOUNT
Accounts held by a specific Party.
Party Address Rel
C_RL_PARTY_ADDRESS
Party to Address relationship.
Party Electronic Address
C_PARTY_ELECT_ADDR
Email and Web Addresses for Parties.
Valid_ind
For example does the address
include a valid extension (such
as .org or .com)
Opt-in
A privacy preference indicating
which email addresses may be
used to contact the Party, if any.
Party Group
C_PARTY_GROUP
Used to group parties (for example,
group individuals into Households,
group organizations by Account Owner)
Gender
Used to downgrade Name for
females on a merge. For
example merging Ms. Smith
with Mr. Brown: the household
will take the male's name.
Base Objects
7
Party Data Model Base Objects
Display Name
Table Name
Description
Party Group Rel
C_RL_PARTY_GROUP
Links the Party to all the Groups to
which the person or organization
belongs.
Party ID
C_PARTY_ID
Party Id tracks the different identifiers
for Parties used across the various
source systems.
Party Name
C_PARTY_NAME
Supports B2B and Counterparty. A
company may be known as one name
in one system (pre-acquisition name)
and another name in a different system
(post-acquisition). The model allows the
records to be merged while maintaining
multiple names for the same Party
Party Phone
C_PARTY_PHONE
Phone numbers of Parties
Valid Ind
For US phone numbers.
Do Not Call
May be set to Yes for work and
No for Home (for example, if an
Individual states that they do
not wish to be disturbed at
work).
8
Party Preference
C_PARTY_PREFERENCE
Indicates how a Party prefers to be
contacted (which Communication Type
and which Channel). Can also indicate
inbound communication (that is,
'touchpoints'-the channels and
communication types the customer
used).
Party Rel
C_RL_PARTY
Party-to-Party relationships, including
Parent, Affiliate, and Contact.
Person Details
C_PERSON_DETAILS
Enrichment data for Individuals. The
core data for the individual is held on
the Party base object. The data on this
child are less likely to need to be
merged than the data on the Party base
object-and keeping the details separate
helps increase performance.
Chapter 3: Data Model and Schema Configuration
Party Data Model Base Objects
Display Name
Table Name
Description
Data may come from 3rd party systems.
Product Data Model Base Objects
Display Name
Table Name
Description
Product
C_PRODUCT
Products specific to the vertical. Includes Product Groups.
Party to Product Rel
C_RL_PARTY_PRODUCT
Relationship between Party and Product.
Product Attribute
C_PRODUCT_ATTRIBUTE
The attributes for the product (name-pair table). This model provides
flexibility to have different attributes for each vertical.
Product Rel
C_RL_PRODUCT
Product to Product relationship (includes Product-to-Product Group
relationship).
Product to Product
Attribute Rel
C_RL_PROD_PROD_ATTR
The Attributes for a specific Product.
Display Name
Table Name
Description
LU Address Type
C_LU_ADDRESS
Lookup table for types of Addresses such as 'B'='Bill To Address',
'S'='Ship-To Address'.
LU Channel
C_LU_CHANNEL
Lookup table for channels (form of interaction between customer and
business) such as Online, Store, Kiosk, Phone, and so on.
LU Communication
Type
C_LU_COMM_TYPE
Lookup table for types of Communication such as Email, Phone, Inperson, Mail.
LU Country
C_LU_COUNTRY
Lookup table for Country Codes. Different systems may use different
values for county code (for example, ISO 2, ISO 3, and Country
Name).
LU Electronic Address
Type
C_LU_ELECT_ADDR
Lookup table for types of email addresses, such as Web Site, Home,
and Business.
LU Gender
C_LU_GENDER
Lookup table for gender codes such as M, F, and U (male, female,
unknown).
LU Generation Suffix
C_LU_GEN_SUFFIX
Lookup table for generation suffix such as I, II, III (1st, 2nd, 3rd).
LU Identification Type
C_LU_ID_TYPE
Lookup table for ID type.
LU Marital Status
C_LU_MARITAL_STATUS
Lookup table for marital status such as M (married), S (single), and
D (divorced).
LU Name Prefix
C_LU_NAME_PREFIX
Lookup table for name prefix such as Mr., Dr., Ms.
Lookup Base Objects
Base Objects
9
Lookup Base Objects
Display Name
Table Name
Description
LU Phone Type
C_LU_PHONE
Lookup table for type of phone number such as Home, Work,
Business Cell, and Personal Cell.
LU Product Status
C_LU_PRODUCT_STATUS
Lookup table for status of product such as End of life, Discontinued,
and Recalled.
LU Product Type
C_LU_PRODUCT
Lookup table for product type. Used to group products.
LU Standard Industry
Code
C_LU_SICCODE
Lookup Table for SIC codes such as:
0100
Agricultural Production-Crops
0700
Agricultural Services
0800
Forestry
LU State
C_LU_STATE
Lookup table for state codes.
Hierarchy Manager Base Objects
10
Display Name
Table Name
Description
Rbo Bo Class
C_RBO_BO_CLASS
HM table for Entity Types.
Rbo Hierarchy
C_RBO_HIERARCHY
HM table for Hierarchy Types.
Rbo Rel Type
C_RBO_REL_TYPE
HM table for Hierarchy Relationship Types.
Chapter 3: Data Model and Schema Configuration
Landing Tables
The following tables describe the landing tables that are defined in the Informatica MDM sample ORS:
Legacy System Landing Tables
Display Name
Table Name
Description
LGC Customer
C_LD_LGC_CUSTOMER
Landing table for Legacy Party data.
LGC Customer to Account
C_LD_LGC_CUST_TO_ACCT
Landing table with Customer to Account
hierarchy data.
LGC Customer to Customer
C_LD_LGC_CUST_TO_CUST
Landing table with Customer to
Customer hierarchy data.
SFA System Landing Tables
Display Name
Table Name
Description
SFA Account
C_LD_SFA_ACCOUNT
Landing table for SFA Account data.
SFA Address
C_LD_SFA_ADDRESS
Landing table for SFA Address data.
SFA Customer
C_LD_SFA_CUSTOMER
Landing table for SFA Party, Household and Group data.
SFA Email Address
C_LD_SFA_EMAIL
Landing table for SFA Email data.
SFA Note
C_LD_SFA_NOTE
Landing table for SFA Notes data.
SFA Party to Party
C_LD_SFA_PARTY_PARTY
Landing table for SFA Party hierarchy data.
SFA Party to Product
C_LD_SFA_PARTY_PRODUCT
Landing table for SFA Party to Product hierarchy data.
SFA Privacy
Preference
C_LD_SFA_PRIV_PREF
Landing table for SFA Privacy Preference data.
SFA Telecom
C_LD_SFA_TELECOM
Landing table for SFA phone number data.
Product System Landing Tables
Display Name
Table Name
Description
Product Data
C_LD_PRODUCT_DATA
Landing table for Product data.
ODI System Landing Tables
Display Name
Table Name
Description
ODI Tree
C_LD_ODI_TREE
Landing table for all ODI data.
Landing Tables
11
Staging Tables
The following tables describe the staging tables that are defined in the Informatica MDM sample ORS:
Party Data Model Stage Tables
12
Base Object
Display Name
Table Name
Source System
Account
None
Address
ODI Address
C_SG_ODI_ADDRESS
ODI
Address
LGC Billing Address Stg
C_SG_LGC_BILL_ADDRESS
Legacy
Address
LGC Shipping Address Stg
C_SG_LGC_SHIP_ADDRESS
Legacy
Address
SFA Address Stg
C_SG_LGC_ADDRESS
SFA
Organization Details
ODI Organization Details
C_SG_ODI_ORG_DTL
ODI
Organization Standard
Industry Code
None
Party
ACX Party
C_SG_ACX_PARTY
Acxiom
Party
ODI Party
C_SG_ODI_PARTY
ODI
Party
LGC Party Stg
C_SG_LGC_PARTY
Legacy
Party
SFA Party Stg
C_SG_SFA_PARTY
SFA
Party Account Relationship
None
Party Address Rel
ODI Party Address Rel
C_SG_ODI_PARTY_ADDR
ODI
Party Address Rel
LGC Party to Billing Address Stg
C_SG_LGC_PTY_BILL_ADDR
Legacy
Party Address Rel
LGC Party to Shipping Address
Stg
C_SG_LGC_PTY_SHIP_ADDR
Legacy
Party Address Rel
SFA Party to Address Stg
C_SG_SFA_PTY_ADDR
SFA
Party Electronic Address
SFA Electronic Address Stg
C_SG_SFA_ELECT_ADDRESS
SFA
Party Group
LGC Household Stg
C_SG_LGC_HOUSEHOLD
Legacy
Party Group
SFA Household Stg
C_SG_SFA_HOUSEHOLD
SFA
Party Group Rel
LGC Party Group Rel Stg
C_SG_LGC_GRP_REL
Legacy
Party Group Rel
SFA Party Group Rel Stg
C_SG_SFA_GRP_REL
SFA
Party ID
None
Party Name
None
Chapter 3: Data Model and Schema Configuration
Party Data Model Stage Tables
Base Object
Display Name
Table Name
Source System
Party Phone
ODI Party Phone
C_SG_ODI_PARTY_PHONE
ODI
Party Phone
SFA Party Phone Stg
C_SG_SFA_PARTY_PHONE
SFA
Party Preference
None
Party Rel
ODI Parent/HQ
C_SG_ODI_PARENT_HQ
ODI
Party Rel
SFA Party Rel Stg
C_SG_SFA_PARTY_REL
SFA
Person Details
None
Product Data Model Stage Tables
Base Object
Display Name
Table Name
Source System
Product
PRD Product
C_SG_PRD_PRODUCT
Product
Product
SFA Account Stg
C_SG_SFA_PRODUCT
SFA
Party to Product Rel
SFA Party to Product Rel
C_SG_SFA_PTY_PROD_REL
SFA
Product Attribute
None
Product Rel
PRD Product Rel
C_SG_PRD_PRODUCT_REL
Product
Product to Product Attribute
Rel
PRD Product to Product Attribute
C_SG_PRD_PROD_ATTRIBUTE
Product
Lookup Stage Tables
Base Object
Display Name
Table Name
Source System
LU Address Type
LK Address Type
C_SG_LK_ADDRESS_TYPE
Lookups
LU Channel
None
LU Communication Type
None
LU Country
LK Country
C_SG_LK_COUNTRY
LU Electronic Address Type
LK Electronic Address
C_SG_LK_ELECT_ADDR
LU Gender
LK Gender
C_SG_LK_GENDER
LU Generation Suffix
LK Generation Suffix
C_SG_LK_GEN_SUFFIX
LU Identification Type
None
LU Marital Status
LK Marital Status
C_SG_LK_MARITAL_STATUS
Staging Tables
13
Lookup Stage Tables
14
Base Object
Display Name
Table Name
LU Name Prefix
LK Name Prefix
C_SG_LK_NAME_PREFIX
LU Phone Type
LK Phone Type
C_SG_LK_PHONE
LU Product Status
LK Product Status
C_SG_LK_PRODUCT_STATU
S
LU Product Type
LK Product Type
C_SG_LK_PRODUCT_TYPE
LU Standard Industry Code
None
LU State
LK State
Chapter 3: Data Model and Schema Configuration
C_SG_LK_STATE
Source System
CHAPTER 4
Data Cleansing Configuration
This chapter includes the following topics:
¨ Source System Cleanse Maps, 15
¨ Cleanse Functions, 18
Source System Cleanse Maps
One of the primary methods to bring data into the Informatica MDM Hub from source systems is through the land,
stage, and load processes. During the stage process, the data can be modified by data standardization routines,
such as routines that remove erroneous characters, and other data quality procedures. This process is referred to
as data cleansing.
Cleanse maps define the rules for how to move data from landing tables to staging tables. These maps are based
on one landing table and one staging table. Each field in the landing table can be directly mapped to a field in the
staging table or the field can be modified by mapping it through one or more cleanse functions before mapping it to
the staging table field. A typical cleanse routine found on a cleanse map might remove excess spaces (trim) from
the data, or change all of the characters in a string field to uppercase.
These maps are also called stage maps and are executed using a batch process by running the stage job
associated with the specific staging table used by the map. The maps can also be called in real-time through calls
to the SIF API.
The cleanse maps defined in the sample ORS are listed in the table below.
Source
Landing Table
Mapping Name
Stage Table
Legacy
LGC Customer
LGC Billing Address
LGC Billing Address Stg
LGC Customer
LGC Household
LGC Household Stg
LGC Customer
LGC Household to Party
LGC Party Group Rel Stg
LGC Customer
LGC Party
LGC Party Stg
LGC Customer
LGC Party to Billing Address
LGC Party to Billing Address Stg
LGC Customer
LGC Party to Shipping Address
LGC Party to Shipping Address Stg
LGC Customer
LGC Shipping Address Stg
LGC Shipping Address Stg
15
Source
Landing Table
Mapping Name
Stage Table
SFA
SFA Account
SFA Account
SFA Account Stg
SFA Account
SFA Address
SFA Address Stg
SFA Account
SFA Party to Address
SFA Party to Address Stg
SFA Customer
SFA Household
SFA Household Stg
SFA Customer
SFA Party
SFA Party Stg
SFA Customer
SFA Party Group Rel
SFA Party Group Rel Stg
SFA Email
Address
SFA Electronic Address
SFA Electronic Address Stg
SFA Telecom
SFA Party Phone
SFA Party Phone Stg
SFA Party to
Product
SFA Party to Product
SFA Party to Product Rel
Lookup
Product Data
LU Product
LK Product
Product
Product Data
PRD Product
PRD Product
Product Data
PRD Product Rel
PRD Product Rel
Product Data
PRD Product to Product Attribute
PRD Product to Product Attribute
ODI Tree
ODI Address
ODI Address
ODI Tree
ODI Organization Details
ODI Organization Details
ODI Tree
ODI Parent / HQ
ODI Parent / HQ
ODI Tree
ODI Party
ODI Party
ODI Tree
ODI Party Address Rel
ODI Party Address Rel
ODI Tree
ODI Party Phone
ODI Party Phone
ODI
16
Chapter 4: Data Cleansing Configuration
Some cleanse maps are simple while others are complex, using multiple custom cleanse functions. Examples of
cleanse maps, one simple and one complex, are shown below.
Source System Cleanse Maps
17
A sample of the custom cleanse functions used on the cleanse maps is defined in the section "Cleanse Functions."
Cleanse Functions
Informatica MDM Hub comes with a standard set of cleanse functions that consist of common string manipulation
functions, logical operations, data conversion functions, and pre-built cleanse lists (a specific type of cleanse
function). You can combine these standard functions into custom functions that perform data manipulation specific
to the data cleanse requirements of a particular source system.
A number of custom cleanse functions have been created as part of the sample ORS configuration. These
functions can be found in the Cleanse Function tool. They are stored in the Custom, CustomUtilityLibrary, and
General Processing folders. There are also some sample cleanse lists in the Noise Filters folder.
In addition to these custom functions, the sample ORS contains cleanse function libraries (folders) for third-party
data quality tools (for example, Address Doctor 5) and third-party data service providers. You can access the
functionality of these products using special adapters developed on the Informatica MDM Open Cleanse
architecture that allows for plugging-in third-party data quality tools.
These third-party cleanse adapters can be purchased separately, as needed, from Informatica. For more details,
please contact your Informatica Account Manager.
18
Chapter 4: Data Cleansing Configuration
Note: The cleanse functions based on these products will not function unless the underlying third-party software
and Informatica MDM cleanse adapter is correctly installed and configured on your system.
Cleanse Address - NA
This cleanse graph function is used to cleanse North American (NA) addresses. It combines the AddressDoctor 5
cleanse function with other cleanse functions to create a complex function that is used as a component of the
address cleanse maps. The function can also be called as a stand alone service through the SIF API.
Cleanse Functions
19
Parse Phone Number - NA
This cleanse graph function parses phone numbers into the different components of a North American phone
number.
20
Chapter 4: Data Cleansing Configuration
CHAPTER 5
Match and Merge Configuration
This chapter includes the following topics:
¨ Trust Settings, 21
¨ Trust Validation Rules, 24
¨ Match Rule Configuration, 25
Trust Settings
The tables in this section provide the trust settings for the following base objects of the sample schema:
¨ Party
¨ Party Group
¨ LU Country
¨ LU State
¨ LU Electronic Address Type
Base Object: Party
Attribute
Source System
Initial Trust
Min Trust
Decay Period
Decay Curve
Name Prefix Cd
SFA
80
40
3 Years
SIRL
Legacy
70
30
4 Years
Linear
Admin
90
20
5 Years
Linear
SFA
80
40
3 Years
SIRL
Legacy
70
30
4 Years
Linear
Admin
90
20
5 Years
Linear
SFA
80
40
3 Years
SIRL
Legacy
70
30
4 Years
Linear
Admin
90
20
5 Years
Linear
First Name
Last Name
21
Base Object: Party
Attribute
Source System
Initial Trust
Min Trust
Decay Period
Decay Curve
Middle Name
SFA
80
40
3 Years
SIRL
Legacy
70
30
4 Years
Linear
Admin
90
20
5 Years
Linear
SFA
80
40
3 Years
SIRL
Legacy
70
30
4 Years
Linear
Admin
90
20
5 Years
Linear
Birthdate
Admin
90
20
5 Years
Linear
Gender Cd
SFA
80
40
3 Years
SIRL
Legacy
70
30
4 Years
Linear
Admin
90
20
5 Years
Linear
SFA
80
40
3 Years
SIRL
Legacy
70
30
4 Years
Linear
Admin
90
20
5 Years
Linear
SFA
80
40
3 Years
SIRL
Legacy
70
30
4 Years
Linear
ODI
85
40
5 Years
Linear
Admin
90
20
5 Years
Linear
SFA
80
40
3 Years
SIRL
Legacy
70
30
4 Years
Linear
ODI
85
40
5 Years
Linear
Admin
90
20
5 Years
Linear
Generation Suffix
Cd
Status Cd
Display Name
Organization
Name
Base Object: Party Group
22
Attribute
Source System
Initial Trust
Min Trust
Decay Period
Decay Curve
Name
SFA
0
0
12 Months
SIRL
Legacy
70
30
4 Years
Linear
Chapter 5: Match and Merge Configuration
Base Object: Party Group
Attribute
Gender
Source System
Initial Trust
Min Trust
Decay Period
Decay Curve
Admin
90
20
5 Years
Linear
SFA
80
40
3 Years
SIRL
Legacy
70
30
4 Years
Linear
Admin
90
20
5 Years
Linear
Base Object: LU Country
Attribute
Source System
Initial Trust
Min Trust
Decay Period
Decay Curve
Country Code
Lookups
90
90
10 Years
Linear
Admin
0
0
12 Months
Linear
Lookups
90
90
10 Years
Linear
Admin
0
0
12 Months
Linear
Lookups
90
90
10 Years
Linear
Admin
0
0
12 Months
Linear
Lookups
90
90
10 Years
Linear
Admin
0
0
12 Months
Linear
Lookups
90
90
10 Years
Linear
Admin
0
0
12 Months
Linear
Country Code ISO3
Country Code Num
Country Code
Disp
Country Code
Desc
Base Object: LU State
Attribute
Source System
Initial Trust
Min Trust
Decay Period
Decay Curve
State Code
Lookups
90
90
10 Years
Linear
Admin
0
0
12 Months
Linear
Trust Settings
23
Base Object: LU State
Attribute
Source System
Initial Trust
Min Trust
Decay Period
Decay Curve
Phone Type Disp
Lookups
90
90
10 Years
Linear
Admin
0
0
12 Months
Linear
Base Object: LU Electronic Address Type
Attribute
Source System
Initial Trust
Min Trust
Decay Period
Decay Curve
Electronic Type
Lookups
90
90
10 Years
Linear
Admin
0
0
12 Months
Linear
Lookups
90
90
10 Years
Linear
Admin
0
0
12 Months
Linear
Lookups
90
90
10 Years
Linear
Admin
0
0
12 Months
Linear
Country Code
Disp
Country Code
Desc
Note: Other lookup base objects have similar trust settings.
Trust Validation Rules
The "Downgrade Unknown Gender" Trust Validation rule on the Party base object downgrades the name fields
and the Gender Code field if the Gender code is not "M" or "F".
Rule Name:
Downgrade Unknown Gender
Rule Type:
Domain Check
Rule Columns
Downgrade Percentage
First Name
20
Last Name
20
Gender Cd
20
Middle Name
20
Validation Rule SQL:
WHERE S.GENDER_CD NOT IN( 'M', 'F' )
24
Chapter 5: Match and Merge Configuration
Match Rule Configuration
Match rules can be set up in Informatica MDM to match and merge the duplicate records not only from different
source systems but also from within the same source. Match rules can be set up using attributes from any related
base object tables in the Informatica MDM target data model. Below are the steps and components involved in
defining Match rules.
1.
Identify the Base Objects that need data Matched and Merged.
2.
Determine if a Base Object requires Fuzzy Match capabilities.
3.
Define Path to related base objects.
4.
Define Match Columns for the Base Object. Attributes from related base objects can be used only if a Path is
setup first.
5.
Define Match Rule Sets if different Match Rules need to be run at different times.
6.
Create Match Rules using the various combinations of Match Columns.
7.
Set Match Rules as Auto-Merge or Manual rules depending on the precision of the match rule.
Here are the base objects that are configured for matching in the Sample Schema:
Party
Match rules for Individual and Organization data
Match data based on name and address
Address
Match based on address information
Party Address Rel
Match based on Party and Address IDs and Address Type.
Party Group
Match based on group type and address
Party Group Rel
Match based on Party and Party Group IDs, Hierarchy and Rel Type
Product
Match based on Product Name and Number
Note: The match configuration for the Party and Address base objects are detailed in the next two sections.
Match Columns & Rules for Party Base Object
The match paths, match columns, rule sets, match rules, and fuzzy key settings for the Party base object are
defined in the following tables:
Party Match Path Settings
Display Name
Component Name
Table Name
Direction
Check
Missing Child
Root
N/A
Party
N/A
N/A
Person Details
C_MT_PERSON_DETAILS
Person Details
Parent-to-Child
Yes
Match Rule Configuration
25
Party Match Path Settings
Display Name
Component Name
Table Name
Direction
Check
Missing Child
Party Address Rel
C_MT_PARTY_ADDRESS_REL
Party Address Rel
Parent-to-Child
Yes
Address
C_MT_ADDRESS
Address
Child-to-Parent
Yes
Party Name
C_MT_PARTY_NAME
Party Name
Parent-to-Child
Yes
Telecom
C_MT_TELECOM
Party Phone
Parent-to-Child
Yes
Electronic Address
C_MT_ELECTRONIC_ADDRESS
Party Electronic
Address
Parent-to-Child
Yes
Org Details
C_MT_ORG_DETAILS
Organization Details
Parent-to-Child
Yes
Party Fuzzy Match Key Settings
Key Type
Key Width
Source Table
Organization_Name
Extended
Party
Match columns need to be defined in order to identify which columns from the base object is used in the match
rules. Match column types can be exact or fuzzy. It is also possible to assign multiple columns for the base object
to one match column. This is necessary when a fuzzy match column is expecting data that is stored in different
columns in the base object. Match columns can also be assigned columns from a child table to the base object.
Party Match Columns
Match Column Name
Column Type
Path Component
Source Table
Selected Columns
Address_Part1
Fuzzy
Address
Address
Address Line1
Address Line2
Address_Part2
Fuzzy
Address
Address
City Name
State Cd
26
Attribute1
Fuzzy
Electronic Address
Party Electronic
Address
Electronic Address
Ex_Address_Type
Exact
Party Address Rel
Party Address Rel
Address Type
Ex_Birthdate
Exact
Root
Party
Birthdate
Ex_Electronic_Address
Exact
Electronic Address
Party Electronic
Address
Electronic Address
Ex_Generation
Exact
Root
Party
Generation Suffix Cd
Ex_Party_Type
Exact
Root
Party
Party Type
Chapter 5: Match and Merge Configuration
Party Match Columns
Match Column Name
Column Type
Path Component
Source Table
Selected Columns
Ex_Telecom
Exact
Telecom
Party Phone
Phone Number
Id
Fuzzy
Root
Party
Tax ID
Organization Name
Fuzzy Match Key
Root
Party
Display Name
Person_Name
Fuzzy
Root
Party
Display Name
Postal_Area
Fuzzy
Address
Address
Postal Cd
Postal_Sub3
Exact
Address
Address
Postal - Sub3
SSA_Date
Fuzzy
Root
Party
Birthdate
Telephone_Number
Fuzzy
Telecom
Party Phone
Phone Number
Party IDL Match Rule Set
Search Level
Enable Search by Rules
Enable Filtering
Exhaustive
No
No
Party IDL Match Rules
Rule #
Auto
Type
Accept Limit
Adjustment
Match Purpose
(Match Level)
Columns
1
Yes
Fuzzy
0
Division (Typical)
Address_Part1
Address_Part2
Ex_Party_Type {Organization}
Organization_Name
Postal_Area
2
Yes
Fuzzy
0
Resident
(Conservative)
Address_Part1
Address_Part2
Ex_Generation Ø↔Ø
Ex_Party_Type {'Person'}
Person_Name
Postal_Area
3
No
Fuzzy
0
Individual (Typical)
Ex_Generation Ø↔Ø
Ex_Party_Type {'Person'}
ID
Person_Name
SSA_Date
4
No
Fuzzy
10
Division (Loose)
Address_Part1
Address_Part2
Match Rule Configuration
27
Party IDL Match Rules
Rule #
Auto
Type
Accept Limit
Adjustment
Match Purpose
(Match Level)
Columns
Ex_Party_Type {Organization}
Organization_Name
Postal_Area
5
No
Fuzzy
0
Organization
(Typical)
Ex_Party_Type {Organization}
Ex_Telecom
Organization_Name
6
No
Fuzzy
-10
Resident (Typical)
Address_Part1
Ex_Party_Type {person}
Person_Name
Postal_Area
7
No
Fuzzy
0
Person_Name
(Typical)
Ex_Birthdate
Ex_Party_Type{'Person'}
Person_Name
8
No
Fuzzy
0
Person_Name
(Typical)
Ex_Electronic_Address
Ex_Party_Type{'Person'}
Person_Name
9
No
Fuzzy
0
Person_Name
(Typical)
Ex_Party_Type{'Person'}
Ex_Telecom
Person_Name
10
No
Fuzzy
0
Organization
(Typical)
Address_Part1
Address_Part2
Organization_Name
Postal_Area
Postal_Sub
Party WS Match Rule Set
Search Level
Enable Search by Rules
Enable Filtering
Exhaustive
Yes
No
Party WS Match Rules
28
Rule #
Auto
Type
Accept Limit
Adjustment
Match Purpose
(Match Level)
Columns
1
Yes
Fuzzy
0
Division (Typical)
Address_Part1
Address_Part2
Chapter 5: Match and Merge Configuration
Party WS Match Rules
Rule #
Auto
Type
Accept Limit
Adjustment
Match Purpose
(Match Level)
Columns
Organization_Na
me Postal_Area
2
Yes
Fuzzy
0
Resident (Loose)
Address_Part1
Address_Part2
Person_Name
Postal_Area
3
No
Fuzzy
0
Organization
(Typical)
Organization_Na
me
4
No
Fuzzy
0
Person_Name
(Typical)
Person_Name
Postal_Area
Address Match Columns & Rules
The match paths, match columns, rule sets, match rules, and fuzzy key settings for the Address base object are
defined in the following tables:
Address Match Path Settings
Display Name
Component Name
Table Name
Direction
Check Missing Child
Root
N/A
address
N/A
N/A
Address Fuzzy Match Key Settings
Key Type
Key Width
Source Table
Address_Part1
Standard
Address
Address Match Columns
Match Column Name
Column Type
Path Component
Source Table
Selected Columns
Address_Part1
Fuzzy Match Key
Root
Address
Address Line1
Address Line2
Address_Part2
Fuzzy
Root
Address
City Name
State Cd
Ex_Address_Line_1
Exact
Root
Address
Address Line1
Ex_City
Exact
Root
Address
City Name
Ex_Postal_Code
Exact
Root
Address
Postal Cd
Match Rule Configuration
29
Address Match Columns
Match Column Name
Column Type
Path Component
Source Table
Selected Columns
Ex_State
Exact
Root
Address
State Cd
Postal_Area
Fuzzy
Root
Address
Postal Cd
Address IDL Match Rule Set
Search Level
Enable Search by Rules
Enable Filtering
Typical
No
No
Address IDL Match Rules
Rule #
Auto
Type
Accept Limit
Adjustments
Match Purpose
(Match Level)
Columns
1
Yes
Exact
--
--
Ex_Address_Line1
Ex_City Ø↔Ø
Ex_Postal_Code
Ex_State Ø↔Ø
2
No
Fuzzy
0
Address (Typical)
Address_Part1
Address_Part2
Postal_Area
Party Group Match Columns & Rules
The match paths, match columns, rule sets, match rules and fuzzy key settings for the Party Group base object
are defined in the following tables:
Party Group Match Path Settings
30
Display Name
Component Names
Table Name
Direction
Check Missing
Child
Root
N/A
Party Group
N/A
N/A
Group to Party
C_MT_GROUP_TO_PARTY
Party Group Rel
Parent-to-Child
Yes
Party
C_MT_PARTY
Party
Child-to-Parent
Yes
Chapter 5: Match and Merge Configuration
Party Group Match Path Settings
Display Name
Component Names
Table Name
Direction
Check Missing
Child
Party to Address
C_MT_PARTY_TO_ADDRESS
Party Address
Rel
Parent-to-Child
Yes
Address
C_MT_ADDR
Address
Child-to-Parent
Yes
Party Group Fuzzy Match Key Settings
Key Type
Key Width
Source Table
Address_Part1
Standard
Address
Party Group Match Columns
Match Column Name
Column Type
Path Component
Source Table
Selected Columns
Address_Part1
Fuzzy Match Key
Address
Address
Address Line1
Address Line2
Address_Part2
Fuzzy
Address
Address
City Name
State Cd
Ex_Address1
Exact
Address
Address
Address Line1
Ex_City
Exact
Address
Address
City Name
Ex_State
Exact
Address
Address
State Cd
Ex_Group_Type
Exact
Root
Party Group
Group Type
Postal_Area
Fuzzy
Address
Address
Postal Cd
Party Group IDL Match Rule Set
Search Level
Enable Search by Rules
Enable Filtering
Typical
No
No
Party Group IDL Match Rules
Rule #
Auto
Type
Accept
Limit
Adjustme
nt
Match Purpose
(Match Level)
Columns
1
Yes
Exact
--
--
Ex_Address_Line1
Ex_City
Match Rule Configuration
31
Party Group IDL Match Rules
Rule #
Auto
Type
Accept
Limit
Adjustme
nt
Match Purpose
(Match Level)
Columns
Ex_State
Ex_Group_Type
2
No
Fuzzy
0
Address
(Conservative)
Address_Part1
Address_Part2
Ex_Group_Type
Postal_Area
32
Chapter 5: Match and Merge Configuration
CHAPTER 6
Hierarchy Manager (HM)
Configuration
This chapter includes the following topics:
¨ Entity Objects and Types, 33
¨ Hierarchies, 34
¨ Relationship Objects and Types, 34
¨ Hierarchy Manger Console, 35
Entity Objects and Types
Entity objects have been defined for the following base objects:
¨ Account
¨ Party
¨ Party Group
¨ Product
An entity object is a base object that has been configured to store information about HM entities.
The following entity types have been defined:
Entity Object
Entity Types
Account
Credit Card
Party
Organization
Person
Party Group
Household
Product
Product
Product Group
33
Hierarchies
A hierarchy is logical grouping of relationship types. Hierarchies allow you to group the same data into multiple
hierarchy structures.
The following hierarchies have been defined for the sample schema:
¨ Customer
¨ ODI
¨ Product
Relationship Objects and Types
A relationship object is a base object that has been configured to store information about HM relationships.
Relationship objects have been defined for the following base objects:
¨ Party Account Relationship
¨ Party Group Rel
¨ Party Rel
¨ Party to Product Rel
¨ Product Rel
The following Relationship Types have been defined:
Relationship Object
Entity Types
Party Account Relationship
Party Group Rel
Contains member
Party Rel
Employs
is ODI parent of
Party to Product Rel
Person owns product
Person owns Product Group
Product Rel
Product Group is parent of Product
Product Group is parent of Product Group
Product is parent of Product
34
Chapter 6: Hierarchy Manager (HM) Configuration
Hierarchy Manger Console
The following figure shows the Informatica MDM Hub Hierarchy Manager console:
Hierarchy Manger Console
35