defining data warehouse concepts and terminology chapter 3
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Defining Data Warehouse Concepts and Terminology
Chapter 3
Definition of a Data Warehouse
“ 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 Data Warehouse Method
Data Warehouse Properties
DataWarehouse
Integrated
Time VariantNon Volatile
SubjectOriented
Subject-Oriented
Data is categorized and stored by business subjectrather than by application
EquityPlans Shares Customer
financialinformation
Savings
Insurance
Loans
OLTP Applications Data Warehouse Subject
Integrated
OLTP Applications
SavingsSavings
Currentaccounts
Currentaccounts
LoansLoans
Data Warehouse
Data on a given subject is defined and stored once.
Customer
Time-Variant
Data is stored as a series of snapshots, each representing a period of time
Time DataJan-97 JanuaryFeb-97 FebruaryMar-97 March
Nonvolatile
Typically data in the data warehouse is not updated or delelted.
Insert UpdateDelete
Read Read
Operational Warehouse
Load
Changing Data
Warehouse Database
First time load
Refresh
Refresh
Refresh
Operational Database
Data Warehouse Versus OLTP
PropertyResponseTime
Operations
Nature of Data
Data Organization
Size
Data Source
Activities
OperationalSub seconds to seconds
DML
30-60 days
Applications
Small to large
Operational, Internal
Processes
Data Warehouse
Seconds to hours
Snapshots over time
Subject, time
Large to very large
Operational, Internal,External
Analysis
Primarily read only
Usage Curves
Operational system is predictableData warehouse - Variable - Random
User Expectations
Control expectationsSet achievable targets for query
responseSet SLAsEducateGrowth and use is exponential
Enterprisewide Warehouse
Large scale implementationScope the entire businessData from all subject areasDeveloped incrementallySingle source of enterprisewide dataSingle distribution point to
dependent data marts
Data Warehouses Versus Data Marts
Property Data Warehouse Data MartScope Enterprise DepartmentSubject Multiple Single-subject, LOBData Source Many FewSize(typical) 100 GB to>1 TB <100 GBImplementation time Months to years Months
DataWarehouse
DataWarehouse
DataMartDataMart
Dependent Data Mart
MarketingSales
FinanceHuman Resources
MarketingSales
FinanceHuman Resources
MarketingMarketing
MarketingMarketing
MarketingMarketing
External Data
DataWarehouse
OperationalSystems
Flat Files
Data Marts
Independent Data Mart
OperationalSystems
External Data
Sale or Marketing
Flat Files
Data Warehouse TerminologyOperational data store (ODS) Stores tactical data from production
systems that are subject-oriented and integrated to address operational needs
Metadata
MetadataMetadata
Data Warehouse Terminology
DataIntegration
Enterprise data warehouse
Business areawarehouse
Source data
Architecture
Methodolgy
Ensures a successful data warehouseEncourages incremental developmentProvides a staged approach to an
enterprisewide warehouse - Safe - Manageable - Proven - Recommended
Modeling
Warehouses differ from operational structures: - Analytical requirements - Subject orientationData must map to subject oriented information: - Identify business subjects - Define relationships between subjects - Name the attributes of each subjectModeling is iterativeModeling tools are available
Extraction, Transformation, and Transportation
Purchase specialist tools, or develop programsExtraction-- select data using different methodsTransformation--validate, clean, integrate, and
time stamp dataTransportation--move data into the warehouse
OLTP Databases Staging File Warehouse Database
Data Management
Efficient database server and management tools for all aspects of data management
Imperatives - Productive - Flexible - Robust - EfficientHardware, operating system and network
management
Data Access and Reporting
Tools that retrieve data for business analysis Imperatives - Ease of use - Intuitive - Metadata - Training More than one tool may be required
WarehouseDatabase
Simple Queries
Forecasting
Drill-down
Oracle Warehouse Components
Relational / Multidimensional
Text, image Spatial
Web Audio video
Externaldata
Operational data
Relational tools
OLAP tools
Applications/Web
Any DataAny Source Any Access
Oracle Data Mart Suite
Data ModelingOracle Data Mart Designer
OLTPEngines
OLTPDatabases
DataExtraction
Oracle Data MartBuilder
Ware-housingEngines
Data MartDatabase
SQL*Plus
DataManagement
Oracle EnterpriseManager
Data Access& Analysis
Discoverer &Oracle Reports
Data Mart Implementation with the Oracle Data Mart Suite
Oracle Enterprise ServerOracle Enterprise ManagerOracle Data Mart BuilderOracle Data Mart DesignerOracle DiscovererOracle Web Application ServerOracle Reports
Oracle Warehouse Builder Architecture
Sources
ExtractionFacilities• Loader• Remotes SQL• Gateways - OLE-DB/ODBC - Mainframe - Specialized• ERP Data - SAP - Peoplesoft - Oracle
PL/SQL, JavaTransforms
TransformDriver
PL/SQL, JavaWrapper
ExternalFunctions
TargetTablesFilter
Transform
Oracle 8i
Oracle Business Intelligence Tools
Current Tactical Strategic
IS developsuser’s Views Business users Analysis
Oracle Reports Oracle Discover Oracle Express
The Tool for Each Task
Tool
OracleReports
OracleDiscover
OracleExpress
Productionreporting
Ad hocquery and analysis
Advancedanalysis
Question
What were sales byregion last quarter?
What is driving the increase in NorthAmerican sales?
Given the rapid increasein Web sales, what willtotal sales be for the restof the year?
Task
Oracle Warehouse Services
OracleEducation
OracleConsulting
Oracle Support Services
Customers
SummaryThis lesson covered the following topics:Identifying a common, broadly accepted definition
of the data warehouseDistinguishing the differences between OLTP
systems and analytical systemsDefining some of the common data warehouse
terminologyIdentifying some of the elements and processes in
a data warehouseIdentifying and positioning the Oracle Warehouse
vision, products, and services