Carey Probst Technical Director Technology Business Unit - OLAP Oracle Corporation.

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Presentation transcript:

Carey Probst Technical Director Technology Business Unit - OLAP Oracle Corporation

3 Days: Raw Data to OLAP Session: A Practical Approach for Rapidly Delivering Successful OLAP Solutions

Challenge  Deliver fully-functional OLAP solution in 3 days  Keys to Success: – Existing, populated data source – Well-defined scope of data destined for OLAP – A little knowledge of Oracle Warehouse Builder – A preference for a reporting interface

How Is This Possible? Key points:  Oracle moved the OLAP engine into the database – No need to extract & reload data – Leverage existing designs for OLAP  Automation of complex OLAP design tasks with Oracle Warehouse Builder – Build, Deploy, Load & Query data  Provide several methods of access – SQL access to OLAP – Allowing mix-and-match of OLAP and Relational – Support for multiple access tools & technologies

Oracle Call Interface Relational Technology SQL Engine Object Technology Table Functions OLAP Technology OLAP API Multidimensional Engine Multidimensional Cubes Oracle Database JDBC OLAP Architecture & Terminology Relational Cubes

Step 1: Populated Data Store  Constructing OLAP solutions from warehouses is simple if – Dimensions have been identified – Hierarchies have been identified – Measures are known – Mapping to star schema is simplified – Mapping to OLAP structures streamlined – Many traditionally difficult queries can be easily solved by OLAP

Step 2: Defined Scope of Data  Know what data should logically be summarized for queries  Know types of queries users will want to ask  Known level of aggregation  Known data transformations required

Step 3: Oracle Warehouse Builder  Oracle Warehouse Builder streamlines many complex tasks of building OLAP solution – Design & Metadata population – Deployment of OLAP Cubes – Loading of Data

OLAP Design

OLAP Design – Best Practices  Best Practice Guidelines  Long and Short Descriptions Dimension Attributes: – Level Attribute mapped to column with name suffixed by ‘_LONG_NAME’ or ‘_SHORT_NAME’  Time Dimension Descriptors: – Table name suffixed with ‘_TIME’ – Level Attribute with column suffix ‘_END_DATE’ – Level Attribute with column suffix ‘_TIME_SPAN’ – Level names suffixed with _DAY, _MONTH etc..

OLAP Design - Dimensions

Metadata Design - Cubes

OLAP Deployment

 Deploy scripts using the Deployment Manager  Deploy OLAP metadata via OLAP bridge: – Creates all skeleton objects (empty) – Registered the objects in the OLAP catalog – Binds the OLAP objects to the relational objects – BI Beans enabled environment  Creates a ROLAP environment

Oracle Database OLAP catalog metadata OLAP Deployment OWB Scripts DDL OLAP metadata PL/SQL Generate Create Analytic Workspace Bridge Register Publish Relational Views Register Tables, Dimensions, PLSQL etc.. Deploy

OLAP Deployment - Bridge

OLAP Deployment – Bridge Collection Name-Collection to export OWB Translated Language-MLS Language Deploy to AW-Do you want to create an AW definition AW Name-Name for the AW Generate View Definitions-Do you want to generate views for this AW Generated View Prefix-Prefix for the views Access Type-OLAPI, DISCO (currently ignored) Generated View Directory-Directory on server for generated view script Deploy PLSQL in Database-Do you want to deploy the PLSQL in the db? Username- Password- Hostname- Port- SID- PLSQL Output File-Resultant PLSQL generated Log Level-Information / Trace / Error

OLAP Metadata - OEM

OLAP Data Loading

 Load relational objects via a normal mapping  Load the OLAP Analytic Workspace – Methods:  Mapping – post mapping process  Process Flow activity – Refresh or Insert into Dimensions – Refresh or Insert into Cubes  Using an OWB wrapper procedure on top of the RDBMS PL/SQL

Oracle Database OLAP catalog metadata OLAP Data Loading Analytic Workspace Load/Refresh Relational Views Publish Registered Cubes, Dimensions, Tables Sources Insert/Update

Step 4: Reporting Choices Currently OLAP access is provided through:  BI Beans – The Java query components to enable OLAP – Enables custom application development with several deployment options  Discoverer – The Ad-Hoc query tool now utilizing OLAP – OWB capable of generating Business Areas for Discoverer  SQL – Analytic Workspaces can be queried through SQL  OLAP Worksheet in OWB – Provides visualization during design & build iterations

Ongoing – Maintenance  Add new measures  Add new dimensions or hierarchies  Modify existing hierarchies  Add self calculating measures (formulas)

Add new stored measures  Use Analytic Workspace Manager to define the stored measure  Run add_stored_measure utility to add to an existing Standard Format (SF) cube  Modify SQL views if using SQL queries  Re-run AW enablement for BI Beans if using CWM2 metadata

Add new dimensions or hierarchies  Create new hierarchy  Add descriptions of hierarcy  Populate parent relationship.  Run groupingid to set new hierarchy details  Run hierheight to set new level details  Re-run AW enablement for BI Beans if using CWM2 metadata

Modify existing hierarchies  Make changes to parents, levels, etc. as required.  Run groupingid to set new hierarchy details  Run hierheight to set new level details  Re-run AW enablement for BI Beans if using CWM2 metadata

Add self calculating measures (formulas)  Use Analytic Workspace Manager to define the formula  Run add_cube utility to add to create a new Standard Format (SF) cube  Run set_measure_formula_properties utility to add to the new cube  Modify SQL views if using SQL queries  Re-run AW enablement for BI Beans if using CWM2 metadata

Viewing Data - Samples  BI Beans - Crosstab  Drill to Relational Detail (adhoc jtable)  Ad Hoc query tool  Beanie – Drill to Relational coming  Excel  Discoverer  SQL views – any query tool (olap_table)

BI Beans - Crosstab

Relational Table - jtable

Ad Hoc query tool

Beanie – Oracle Consulting

Excel

Summary  Existing Star schema not required but knowledge of data is  Basic understanding of OWB necessary  OLAP design understanding is critical  Knowledge of OLAP structures and functionality mandatory  Can use Oracle Workflow to automate updates

Next Steps….  Interested in leveraging Oracle OLAP – Joseph Rayman –  – Carey Probst –  – Larry Anderson – 

A Q & Q U E S T I O N S A N S W E R S

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