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Introduction to OWB(Oracle Warehouse Builder) 1 2009-04-01.

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Presentation on theme: "Introduction to OWB(Oracle Warehouse Builder) 1 2009-04-01."— Presentation transcript:

1 Introduction to OWB(Oracle Warehouse Builder) 1 2009-04-01

2 Agenda Data Warehouse o Data Warehouse Concepts o ETL Process Oracle Warehouse Builder(OWB) o OWB Architecture o Data Sources and Data Targets o ETL: Mappings o ETL: Process Flows o Data Quality Management Demonstration o Extracting Data o Data Profiling and Cleansing o Transforming Data

3 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 BuilderOracle OLAP/ Data Miner

4 ETL Process 4 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.

5 OWB Architecture 5

6 Design Centre 6

7 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 7

8 ETL: Mappings 8 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

9 ETL: Process flows 9 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

10 Data Quality Management 10 Data Profiling Missing or invalid values Distributions of the values in a specific column Data Rule for Cleansing

11 Metadata Management 11 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)

12 Demonstration 12 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

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