2 Copyright © Oracle Corporation, All rights reserved. Defining Data Warehouse Concepts and Terminology

2-2 Copyright © Oracle Corporation, All rights reserved. Objectives After completing this lesson, you should be able to do the following: Identify a common, broadly accepted definition of a data warehouse Describe the differences of dependent and independent data marts Identify some of the main warehouse development approaches Recognize some of the operational properties and common terminology of a data warehouse

2-3 Copyright © Oracle Corporation, All rights reserved. Definition of a Data Warehouse “A data warehouse is a subject oriented, integrated, non-volatile, and time variant collection of data in support of management’s decisions.” — W.H. Inmon “An enterprise structured repository of subject- oriented, time-variant, historical data used for information retrieval and decision support. The data warehouse stores atomic and summary data.” — Oracle’s Data Warehouse Definition

2-4 Copyright © Oracle Corporation, All rights reserved.

2-5 Copyright © Oracle Corporation, All rights reserved. Data Warehouse Properties Integrated Time-variantNonvolatile Subject- oriented Data Warehouse

2-6 Copyright © Oracle Corporation, All rights reserved. Subject-Oriented Data is categorized and stored by business subject rather than by application. OLTP Applications Equity Plans Shares Insurance Loans Savings Data Warehouse Subject Customer financial information

2-7 Copyright © Oracle Corporation, All rights reserved. Integrated Data on a given subject is defined and stored once. Data WarehouseOLTP Applications Customer Savings Current Accounts Loans

2-8 Copyright © Oracle Corporation, All rights reserved.

2-9 Copyright © Oracle Corporation, All rights reserved. Data Warehouse Time-Variant Data is stored as a series of snapshots, each representing a period of time.

2-10 Copyright © Oracle Corporation, All rights reserved. Nonvolatile Typically data in the data warehouse is not updated or deleted. Warehouse Read Load Operational Insert, Update, Delete, or Read

2-11 Copyright © Oracle Corporation, All rights reserved. Changing Warehouse Data Operational DatabasesWarehouse Database First time load Refresh Purge or Archive

2-12 Copyright © Oracle Corporation, All rights reserved. Data Warehouse Versus OLTP PropertyOLTPData Warehouse Response TimeSub seconds to seconds Seconds to hours OperationsDMLPrimarily Read only Nature of Data30 – 60 daysSnapshots over time Data OrganizationApplicationSubject, time SizeSmall to largeLarge to very large Data SourcesOperational, InternalOperational, Internal, External ActivitiesProcessesAnalysis

2-13 Copyright © Oracle Corporation, All rights reserved.

2-14 Copyright © Oracle Corporation, All rights reserved. Usage Curves Operational system is predictable Data warehouse: –Variable –Random

2-15 Copyright © Oracle Corporation, All rights reserved. User Expectations Control expectations Set achievable targets for query response Set SLAs Educate Growth and use is exponential

2-16 Copyright © Oracle Corporation, All rights reserved. Enterprisewide Warehouse Large scale implementation Scopes the entire business Data from all subject areas Developed incrementally Single source of enterprisewide data Synchronized enterprisewide data Single distribution point to dependent data marts

2-17 Copyright © Oracle Corporation, All rights reserved. Data Warehouses Versus Data Marts PropertyData WarehouseData Mart ScopeEnterpriseDepartment SubjectsMultipleSingle-subject, LOB Data SourceManyFew Implementation timeMonths to yearsMonths

2-18 Copyright © Oracle Corporation, All rights reserved.

2-19 Copyright © Oracle Corporation, All rights reserved. Dependent Data Mart Data Warehouse Data Marts Flat Files MarketingSalesFinance Marketing Sales Finance HR Operational Systems External Data Operations Data Legacy Data External Data

2-20 Copyright © Oracle Corporation, All rights reserved. Independent Data Mart Sales or Marketing Flat Files Operational Systems External Data Operations Data Legacy Data External Data

2-21 Copyright © Oracle Corporation, All rights reserved. Typical Data Warehouse Components Source Systems Staging Area Presentation Area Access Tools ODS Operational External Legacy Metadata Repository Data Marts Data Warehouse

2-22 Copyright © Oracle Corporation, All rights reserved.

2-23 Copyright © Oracle Corporation, All rights reserved. Warehouse Development Approaches “Big bang” approach Incremental approach: –Top-down incremental approach –Bottom-up incremental approach

2-24 Copyright © Oracle Corporation, All rights reserved. “Big Bang” Approach Analyze enterprise requirements Build enterprise data warehouse Report in subsets or store in data marts

2-25 Copyright © Oracle Corporation, All rights reserved.

2-26 Copyright © Oracle Corporation, All rights reserved. Top-Down Approach Analyze requirements at the enterprise level Develop conceptual information model Identify and prioritize subject areas Complete a model of selected subject area Map to available data Perform a source system analysis Implement base technical architecture Establish metadata, extraction, and load processes for the initial subject area Create and populate the initial subject area data mart within the overall warehouse framework

2-27 Copyright © Oracle Corporation, All rights reserved. Bottom-Up Approach Define the scope and coverage of the data warehouse and analyze the source systems within this scope Define the initial increment based on the political pressure, assumed business benefit and data volume Implement base technical architecture and establish metadata, extraction, and load processes as required by increment Create and populate the initial subject areas within the overall warehouse framework

2-28 Copyright © Oracle Corporation, All rights reserved.

2-29 Copyright © Oracle Corporation, All rights reserved. Incremental Approach to Warehouse Development Multiple iterations Shorter implementations Validation of each phase Strategy Definition Analysis Design Build Production Increment 1 Iterative

2-30 Copyright © Oracle Corporation, All rights reserved. Data Warehousing Process Components Methodology Architecture Extraction, Transformation, and Load (ETL) Implementation Operation and Support

2-31 Copyright © Oracle Corporation, All rights reserved. Methodology Ensures a successful data warehouse Encourages incremental development Provides a staged approach to an enterprisewide warehouse: –Safe –Manageable –Proven –Recommended

2-32 Copyright © Oracle Corporation, All rights reserved. Architecture “Provides the planning, structure, and standardization needed to ensure integration of multiple components, projects, and processes across time.” “Establishes the framework, standards, and procedures for the data warehouse at an enterprise level.” — The Data Warehousing Institute

2-33 Copyright © Oracle Corporation, All rights reserved. Extraction, Transformation, and Load (ETL) “Effective data extract, transform and load (ETL) processes represent the number one success factor for your data warehouse project and can absorb up to 70 percent of the time spent on a typical data warehousing project.” — DM Review, March 2001 SourceTargetStaging Area

2-34 Copyright © Oracle Corporation, All rights reserved. Implementation Data Warehouse Architecture Implementation Ex., Incremental Implementation Increment 1 Increment 2 Increment n...

2-35 Copyright © Oracle Corporation, All rights reserved. Operation and Support Data access and reporting Refreshing warehouse data Monitoring Responding to change

2-36 Copyright © Oracle Corporation, All rights reserved. Phases of the Incremental Approach Strategy Definition Analysis Design Build Production Increment 1 Strategy Definition Analysis Design Build Production

2-37 Copyright © Oracle Corporation, All rights reserved.

2-38 Copyright © Oracle Corporation, All rights reserved. Strategy Phase Deliverables Business goals and objectives Data warehouse purpose, objectives, and scope Enterprise data warehouse logical model Incremental milestones Source systems data flows Subject area gap analysis

2-39 Copyright © Oracle Corporation, All rights reserved. Strategy Phase Deliverables Data acquisition strategy Data quality strategy Metadata strategy Data access environment Training strategy

2-40 Copyright © Oracle Corporation, All rights reserved. Summary In this lesson, you should have learned how to: Identify a common, broadly accepted definition of a data warehouse Describe the differences of dependent and independent data marts Identify some of the main warehouse development approaches Recognize some of the operational properties and common terminology of a data warehouse

2-41 Copyright © Oracle Corporation, All rights reserved. Practice 2-1 Overview This practice covers the following topics: Answering questions regarding data warehousing concept and terminology Discussing some of the data warehouse concept and terminology

2-42 Copyright © Oracle Corporation, All rights reserved.

2-43 Copyright © Oracle Corporation, All rights reserved.

2-44 Copyright © Oracle Corporation, All rights reserved.