E-Business Sales and Purchasing Analysis using Discoverer Relational and Oracle OLAP

Cameron HawthorneAdvantage BI Consulting

17 August 2010

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INTRODUCTION

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Agenda

• What is OLAP ?• Oracle’s OLAP solutions• Case Study – Sunny Queen Farms• Need more information ?• Summary

WHAT IS OLAP ?

What is OLAP ?• On Line Analytical Processing

• Differs from On Line Transaction Processing

• Multi Dimensional OLAP

• Relational OLAP

• Hybrid OLAP

OLAP Features

• Dimensional representation of data

• Hierarchy definitions for dimensions

Sales Channel Hierarchy

OLAP Features

Channel Dimension

All Channels Level

Class Level

Channel Level

OLAP Features

• Pre-Summarised data

Customer – Ship To CodeProduct – SKU Code

Time - Day

OLAP Advantages• Faster reporting of information – query response time

• Business like representation of data to users

• Fast display of rotating dimensions

• Drill down from summarised totals through hierarchies

• Analytical features

OLAP Trade-offs• Additional resources to pre-summarise data

– Time, Disk, Memory

• Management of data sparsity– Cube design, composites of dimension values

• Additional movement of data– From data warehouse or mart to cubes

ORACLE’S OLAP SOLUTIONS

Oracle’s OLAP Solutions• Relational OLAP

– Fact Tables, Dimensions, Materialized Views– Analytical SQL (Rollup, Cube, Group By, Rank etc)

• Multi-Dimensional OLAP– Oracle Express Server– Oracle Database Enterprise Edition OLAP Option– Oracle Hyperion Essbase

• Hybrid OLAP– Cube Organized Materialized Views

OLAP Option Features• Database Enterprise Edition Option

• The OLAP engine runs within the Oracle Database

• Dimensional objects are stored in their native multidimensional format

• Data security is administered in the standard way

• Applications can query dimensional objects using SQL

OLAP Option Features• In the database

– OLAP DML• Functions, Commands, Programs

– Managing AW’s with DBMS_AW Package– Security with grant and revoke– Database backups, flash recovery

• Oracle Warehouse Builder Integration• Analytical Workspace Manager

OLAP Option Features• Data Exploitation Software

– Oracle Business Intelligence 11g– Oracle Discoverer Plus for OLAP– Oracle OLAP Excel Add-In, Simba MDX– Oracle BI Beans – J2EE development– Oracle Application Express– Any SQL Reporting Tool, using 11G OLAP Views

CASE STUDY – SUNNY QUEEN

Sunny Queen Background

• Sunny Queen Farms– 100% Australian Owned company supplying high

quality farm fresh eggs to consumers in all states– Implemented Oracle E-Business Suite in 2001– Selected Oracle Sales Analyzer as reporting solution

• Oracle Express Server database• Windows and web clients• Sales, Rebate, and Case Deal data

SQ Reporting History• 2002 – Changed hierarchies, added budget sales data• 2003 – Added Purchasing actual data analysis• 2004 – Acquired new business – Egg and I, Started archiving• 2005 – Added Purchasing forecast data, changed rebate data focus

to promotional analysis• 2006 – Upgraded to latest version of OSA, changed data model –

new hierarchies and definitions• 2007 – Replacement Discoverer for OLAP solution using Oracle

OLAP Option 10gR1

SQ 2008 Problems• Business model and staff changes over the years led to

data model change requests• Discoverer for OLAP issues:

– Missing OSA functionality– OLAP 10gR1 software bugs causing significant outages– Still relying on OSA during outages– OSA out of support

• Everything on the 1 box– Out of date OS and software patches

2008 OSA Architecture

2008 Disco OLAP Architecture

Current Architecture

Additional details• Data drawn directly from E-Bus schemas

– Requires a knowledge of schemas and tables– Not an E-Bus upgrade-proof solution

• Work-arounds required to meet OWB Basic Edition rules– No Process Flow

• Shell scripting that calls OWB APIs to execute tasks

– No OLAP design integration• Use Analytical Workspace Manager to design and build cubes

Sales Analysis• Sales measured in $$$ and Volume (Units, UOM, Kgs)• Dimensions

– Product – 5 hierarchies incl. Brand, Segment, Size– Geography – Territory and Customer Ownership structures– Channel – Retail, Route Trade, Foodservice– Warehouse – SQ Distribution Centres– Time – Financial and Calendar Years

Purchasing Analysis• Purchases in $$$ and Volume (Units, UOM, Kgs)• Dimensions

– Product – 5 hierarchies incl. Brand, Segment, Size– Grower - Ownership structure– Warehouse – SQ Distribution Centres– Time – Financial and Calendar Years

Margin Analysis• Gross Margin

– Sales $$$ - Purchasing $$$

• Net Margin– Gross Margin $$$ - Estimates of other variables costs $$$

• Needs common dimensions– Product, Warehouse, Time

• Assumes product is sold in same timeframe it is sourced

Variance Analysis• Sales Budgets vs Actuals

– Budgets loaded from .CSV files into Application Express app– Financial estimates of sales performance at high level

• Purchasing Forecasts vs Actuals– Forecasts keyed into Application Express app– Grower estimates at high level

• Provides managers with performance in context

Benefits and Costs• Benefits

– Improved query response times– Stable environment, minimal outages– Minimised impacts on main transaction system– Data model that met current business requirements

• Costs– Additional software licensing– Additional hardware costs

More information

• Oracle OLAP on Oracle Technology Network– www.oracle.com/technetwork/database/options/olap

• Oracle by Example– www.oracle.com/technology/obe/11gr1_db

• Mark Rittman’s blog– www.rittmanmead.com/blog/

• Oracle User Group BI SIG– www.oraclebiwa.org

SUMMARY

Summary

• What is OLAP ?– OLAP Features

• Oracle’s OLAP software– Enterprise Edition OLAP Option

• Sunny Queen Farms Case Study

Contact InformationFor more information about today’s presentation, please contact:

Cameron Hawthorne

Managing Consultant

Advantage BI Consulting

W: www.advantagebi.com.au

E: cameron@advantagebi.com.au

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