Informatica Data Federation Overview

1

Informatica Data Federation Overview

Claudia ChandraProduct Management

2Informatica Confidential and Proprietary

Agenda

• Why Data Federation?

• How It Works

• Customer Use Case Scenarios

• Demo


Enterprise Data IntegrationPhysical data integration

ETL (Extract-Transform-Load) Approach• Extract data from source systems• Integrate, clean, organize, aggregate data via transformation• Store data permanently into target system (usually RDBMS)• Client consumes data from target system (usually via SQL)

Strengths

Holistic Information

Enterprise Platform

Lifecycle Productivity

SOA

Benefits• Data cleansing, rich transformations• Historical data, deterministic results

• Model-driven architecture• Reusable components

• Robust & hardened for large volumes• Protects operational systems

• Collaborative development


Complementary ApproachData federation (EII)

Approach: provides a virtual layer for defining virtual views across multiple data sources for read and write access by applications

• Query data from source systems• Integrate data• Deliver to client via access protocol determined by client (SQL, Web Services,

Java, etc.)

Strengths

Holistic Information

Enterprise Platform

Lifecycle Productivity

SOA

Benefits• Current data delivered on-demand• Unconstrained access

• Rapid development

• Optimized query performance and caching

• Reusable data views abstracted from data sources• Web Services-based data access


Extending Enterprise Data IntegrationData Federation + Physical Data Integration

• Holistic Information• Historical and Current Data

• Cost-Effectively Scale• Greater Flexibility to Optimize Data Architecture• Physically Move Data Based on Proven Demand

• Reduce Time to Results• Faster Response to Business Users• Prototype Virtually, Lock in Requirements, Implement Physically

For many use cases, extending PowerCenter with Data Federation

yields significant benefits

6

Data Federation How It Works


Data Source 1 Data Source 2

Step 1: Build the ViewStep 1: Build the View(A ViewView contains MetadataMetadata on the actual data source – format, type, location, access, etc.)

Data Federation Option– How It WorksCreate View

Data Federation Option View


Data Federation Option View

Data Source 1 Data Source 2

1 A B

2 C D

3 E F

4 G H

1 a b

2 c d

3 e f

4 g h

1 A B a b

2 C D c d

3 E F e f

4 G H g h

Step 2: Aggregate Data(Queries are optimized for speed and efficiency)

Step 3: Deliver DataStep 3: Deliver Data(Combined data creates meaningful information)

Data Federation Option– How It WorksAggregate & Deliver Data

Step 1: Build the View(A View contains Metadata on the actual data source – format, type, location, access, etc.)

Portals BI ToolsWeb Services


PowerCenter Data Federation Option

Business User

Disparate data sources

Issue multiple parallel subqueries

Invoke view; validate security

Generate alternative query plans; pick the best

Format results and return data to client systems

Join, map, and/or aggregate results

Retrieve results from data sources

Display results to userUser requests information through application

Data Federation Option– How It Works

Data Warehouse

RDBMS

XMLPackaged Applications

Web Service

10

Data Federation and PowerCenterUse Case Scenarios


Data Warehouse ExtensionSupplementing with New Data Sources

Data Warehouse

Operational Data

Application

Application

Database

Applications, Portal, BI Tool, etc.

VirtualView

ODBC / JDBC / SOAP

Message Queue

Data Federation

PowerCenter

Real-time data

Approach • Physical: move data

into data warehouse• Federation: combine

information from data warehouse with operational data and data from message queue

Benefit • Accelerate addition of

new data sources to data warehouse

• Combine historical and current data


Next Generation Data Warehouse Prototype and Build

Relational DatabasesFiles

MetadataRepository


Data Warehouse

VirtualView

Data Federation

Power Center

Approach • Federation: create

prototype with virtual views, validate with users

• Physical: with requirements locked in, build robust data integration workflows to create physical data store

Benefit • Accelerate development• Ensure alignment with

user requirements

ODBC / JDBC / SOAP


Next Generation Data MigrationPrototype, Migrate and Insulate

MetadataRepository


Physical Target

Virtual data layer

Data Federation

Approach • Federation: prototype

migration with virtual target, validate

• Physical: migrate the data from the legacy system into the new physical target

• Federation: insulate downstream systems from change

Benefit • Accelerate migration• Make migrations

transparent Legacy

PowerCenter

ODBC / JDBC / SOAP


Data ServicesVirtualization of data sources


Virtual data layer

Data Federation

Approach • Physical: create

physical data stores• Federation: create an

abstraction layer enabling virtual, federated access to data in back-end systems

Benefit • Protect consuming

systems from details of underlying implementation, potential changes

ODBC / JDBC / SOAP

Data Warehouse

Operational Data Store

Application

Application

Database PowerCenter

Application Data


Informatica Differentiators

• Integrated metadata and engine• Reuse logic between data federation and ETL (bi-directional)• Rich ETL transforms—cleansing, etc.

• Universal connectivity• Make heterogeneous data sources available to data federation

• Enterprise performance and scalability• Federated queries on grid

• Metadata-aware data federation• Data lineage • Profiling “metadata”

16

Thank you

Documents

Informatica Data Federation Overview