Retail Data Model

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Oracle Retail Data Model Overview

The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracles products remains at the sole discretion of Oracle.

Retail Data ModelDatabase TechnologyAvailable Today!

Retail Domain Knowledge BI Technology

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Key Messages

Speed to Value

Standards-based, pre-built, pre-tuned data model with intelligent insight into detailed retailer and market data enabling retailers to quickly gain value

Reduced Total Cost of Ownership

Fast, easy and predictable implementation, reduced technology & 3rd Party costs for both immediate and ongoing operations by leveraging pre-built content

Best in class

Modern, topical and relevant Data Model developed using deep retail market expertise with leading Data Warehousing and Business Intelligence technology

4Copyright 2009, Oracle and / or its affiliates. All rights reserved.

Speed to ValueBuild from Scratch with Best of Breed Approach Training & Roll-out Define Metrics & Dashboards

Oracle Retail Data Model

Oracles Approach: Delivers retailer and market insight quickly Rapid implementation, predictable costs lead to higher ROI Combines deep retail market expertise with industry-leading technology

Data MovementTraining & Roll-out Define Metrics & Dashboard Data Movement Easy to Use, Easy to Adapt Comprehensive Retail Measures & Metadata for Business Intelligence Reporting & Ad-hoc Query Automatic Data Movement from your ARTS compliant 3NF schema to OLAP, Mining & Dimensional Schema Pre-built DW Schema (3NF,STAR,OLAP) with Retail best Practice embedded and Pre-tuned for Oracle data warehouses, including the HP Oracle DB Machine

DW DesignDW Design

months or years

weeks or months

5Copyright 2009, Oracle and / or its affiliates. All rights reserved.

Reduced Total Cost of Ownership




Comprehensive Industry Portfolio

Standards-Based Architecture

Designed to Work Together

More Value Less Complexity

More Choice Less Risk

More Flexibility Less Cost

6Copyright 2009, Oracle and / or its affiliates. All rights reserved.

Best-in-classOracle #1 for Retail Oracle #1 for Data Warehousing

Market Size is $6.7 Billion with 14.6% Growth YoY1

7Copyright 2009, Oracle and / or its affiliates. All rights reserved.

Oracle Retail Data ModelAn Overview

Oracle Retail Data Model

Industry Standard Compliant (ARTS) Embedded strong Retail expertise 3NF Logical Data Model Physical Data Model designed & pretuned for Oracle Including Exadata Storage

Oracle Database Enterprise Edition

Oracle Exadata Storage

Industry-specific measures & KPIs Pre-built OLAP models Pre-built Data Mining models Usable within any Retail Application Environment Sample reports and dashboards Based on Oracle BI EE Plus


Data Mining




Oracle Retail Data ModelFoundation for Business Information FlowSell-Side POS (Point-of-Sale) Web stores & Catalog Order Management Inventory Optimization Advertising & Promotions Customer Service Workforce Scheduling Personalized Marketing

Buy-Side Advanced Planning & Scheduling (Demand Driven) Inventory Tracking Pricing Cost Forecasting Purchase Order Mgmt. Retail Partnerships Warehouse Mgmt.

Customer & Consumer Interaction

Retailer Sales Marketing Knowledge Knowledge Knowledge Demand Consumer Knowledge Knowledge

In-Side Manufacturing/Sourcing Sales Forecasting Inventory Tracking Inventory Knowledge Forecasting Knowledge

Product Knowledge


Data WarehouseMfg Perf. Knowledge Sourcing Knowledge



Oracle Retail Data ModelFoundation for Business Information FlowStore-sideRetailer Knowledge Marketing Knowledge Sales Knowledge

Data Warehouse


Consumer Knowledge Demand Knowledge Inventory Knowledge Forecasting Knowledge

Buy-sideSourcing Knowledge Mfg Perf. Knowledge Product Knowledge

10Copyright 2009, Oracle and / or its affiliates. All rights reserved.

Oracle Retail Data ModelIndustry Coverage

Grocery Department Stores Discounters Hard Goods Apparel & Footwear Soft Goods Convenience Stores Gas Stations

11Copyright 2009, Oracle and / or its affiliates. All rights reserved.

Oracle Retail Data ModelKey Statistics

Data Model Contents 650+ Tables and 10,500+ Attributes (ARTS++) Industry-specific 1200+ Measures & KPIs with Business and Technical Definitions 4 Pre-built Analytical Workspaces 12 Pre-built Data Mining Models Automatic Data Movement from 3NF to STAR schema, OLAP Cubes and Data Mining Models Sample Reports & Dashboards using OBIEE Designed and optimized for Oracle data warehouses, including the HP Oracle Database Machine Central repository for atomic level data Rapid implementation

Business Area CoveragePre-Built Measures & KPIsStore Operations Point of Sale Loss Prevention Inventory Category Management Workforce Management Customer Promotion Order Management Store performance, Shopper Conversion, Comparative Store Analysis Multi Channel, POS Flow Unusual Transactions, Hidden Patterns, Attribute Analysis

Merchandising Merchandise Performance, Item-Basket, Fast & Slow Movers Inventory State Analysis, Forecast out-of-stock and zero selling. Product Mix, Shelf Analysis, Customer Purchase vs. Syndicated Data Employee Utilization, SPIFF & Split Commission Analysis Clustering & Segment - Creation, Migration, Analysis Causal Factor, Halo Impact & Promotional Lift Integrated Analytic between e-commerce and Retail

Business Area CoveragePre-Built Measures & KPIsMerchandising Merchandising Role: Commonly a merchant or planner Product stars and dogs Inventory levels vs. planned inventory levels Suppliers that help / hinder performance Identifying locations that over/under perform

Store Operations Store Operations Role: Commonly a store manager Store traffic patterns to determine staffing Understand opportunities to control loss Relative store performance rankings Identify what sells in the stores vs. doesnt Identifying potential risks for out of stocks

Category Management Role: Commonly a Category Manager Controlling purchase costs Reviewing supplier item coverage Understanding consumer purchases of new / current products vs. market data Determining store layouts and planogams

Marketing Role: Commonly a marketing analyst Identify consumer spending habits using market data Analyzing a retailers loyalty program customers to better target campaigns Measuring customer promotion response rates

Oracle Retail Data ModelComponents

Base Layer (3NF)

Derived & Aggregate Layer

Sample Reports

Oracle Retail Data ModelWhy multiple layersIntelligent Interactions (Data Mining)Is the product assortment optimal for all my regions?

Fact-Based Actions (OLAP, Statistics)What are my potential out-of-stock situations?


Performance Management (KPI, Guided Analytics)How is the business doing compared to last year? Compared to plan?




Slice/Dice, Ad-hoc, Query , BI ToolsWhat is my gross margin return on space?

4 3

Transactional ReportingHow are my catalog and internet sales performing?



1Generation Step

Oracle Retail Data ModelAutomatic Data Movement

Oracle Retail Data Model



3NF Base

Intra-ETL Derived (Derived)

Intra-ETL (Aggregate)

OLTP Systems

Source ETL (Data Quality, Staging, Interface)


Leveraging Data Warehouse FeaturesEmbedded as part of VLDB design, not an afterthoughtPartitioning Partitioned Outer Join Reference Architecture Frequent Item Set Advanced Statistics Ranking Lag / Lead

Compression 3-5x Storage Savings

OLAP Time Series Forecasting

Data Mining Classification (ABN/Decision Tree) Association Rules (Apriori)

Materialized Views User Choice SQL Rewritten

Differentiator: Smart Inventory ReportsOut of Stock Forecast (using built-in Forecasting & OLAP cubes numerous methods supported)

OLAP forecasting of sales & inventory to predict potential stock shortage See which forecasting method fits best

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Differentiator: Smart Category ReportProduct Category Mix Analysis: Suggest Items/Categories to Merchandise Together using a Pre-built Mining ModelAnalyzes Sales Transactions using the Association Rules (Apriori) Model to understand the Product Category Mix [If a Customer buys A and C, what is the likelihood the Customer would buy D?]

20Copyright 2009, Oracle and / or its affiliates. All rights reserved.

Why Oracle Retail Data Model?Top 10 Reasons

1 2 3 4 5

Retail expertise with best-in-class technology ARTS based normalized data model

6 7

Easily extendable & customizable model Usable within any retail environment Designed and optimized for VLD