Introduction to OWB(Oracle Warehouse Builder)

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2009-04-01

Agenda• Data Warehouse o Data Warehouse Concepts o ETL Process

• Oracle Warehouse Builder(OWB)o OWB Architectureo Data Sources and Data Targetso ETL: Mappingso ETL: Process Flowso Data Quality Management

• Demonstration o Extracting Datao Data Profiling and Cleansingo Transforming Data

Data Warehouse

3“one of the major ETL tools in the market “

• ETL (Extract/ Transform/ Load)• Data Quality Control• Meta data Management

• Find Pattern• Predict Behaviour or value (Classification/ Regression)• Generate Report

Oracle Warehouse Builder Oracle OLAP/ Data Miner

ETL Process

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• Extract: extract data from sources and put in a so-called Staging Area(SA), usually with the same structure as the source.

• Load: finally, data is loaded into a central warehouse, usually into fact and dimension tables.

• Transform: join and union tables, filter and sort the calculations. In this step, we can check on data quality and cleans the data if necessary.

OWB Architecture

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Design Centre

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• Oracle– Tables, Views, MViews,

Queues, External Tables, Sqlloader, Transportable Tablespaces, Data Pump…

• DB2, Sybase, SQLServer, Informix, Mainframes, … (Oracle Transparent Gateways)

• ODBC• Flat Files• XML• Applications

– Oracle Ebusiness Suite– PeopleSoft– SAP– Siebel

Sources Targets

• Oracle• DB2, Sybase, SQLServer, Informix,

Mainframes, … (Oracle Transparent Gateways)

• ODBC• Flat Files• XML

Data sources and Data Targets

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ETL: Mappings

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• Declarative modeling of Data Flows

• Map from Source to Target• Integrated Data Quality

– N&A standardization– Match/Merge– Profiling

• Generates SQL & PL/SQL– Merge, transportable

tablespaces, data pump, sqlloader, xml data types, BLOBS/CLOBS, …

• Leverage custom data transformations

ETL: Process flows

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• Declarative modeling of Process/work Flows

• Co-ordinate execution of Maps and other activities

• Create complex transitions• Send email, FTP

source/target files, call any external process, SQL Plus, Notifications

• Generates Oracle Workflow, Oracle Scheduler & XPDL

Data Quality Management

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• Data Profiling• Missing or invalid values• Distributions of the values

in a specific column• Data Rule for Cleansing

Metadata Management

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• Dependency Management– Data Lineage at attribute level– Impact Analysis at attribute level

• Metadata Snapshots• Change Management (diff, merge and reconcile)• Reporting (browser)• APIs (Scripting, SQL, PL/SQL)• Exchange (import/export)

Demonstration

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1. Identifying data sources/ targets and importing metadata

3. Data profiling and decide data cleansing strategy

4. Design and execute mappings (Merging) and cleansing

5. Design dimension tables

Define Sources & Targets Extract Data Profiling

Transform Load

“Derived Data Rule”

2. Import data and design and execute mappings (Extract)

“Generated Code”

“Generated Code”