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-- Download Data Warehousing as PDF --


Overview

A Data Warehouse has been used to refer to a database that contains very large stores of historical data. The data is stored as a series of snapshots, in which each record represents data at a specific time. This data snapshot allows a user to reconstruct history and to make accurate comparisons between different time periods.

Typical relational databases are designed for on-line transactional processing (OLTP) and do not meet the requirements for effective on-line analytical processing (OLAP). As a result, data warehouses are designed differently than traditional relational databases.

Typical uses

A data warehouse integrates and transforms the data that it retrieves before it is loaded into the warehouse. A primary advantage of a data warehouse is that it provides easy access to and analysis of vast stores of information.

DEFINITION, ARCHITECTURE AND CONCEPTS

DATA MODELING OPTIONS

IMPLEMENT OPTIONS

EXTRAT, TRANSFORM, LOAD (ETL) TERMS AND CONCEPTS

  • Options
  • Extraction Options
  • Transformation Options
  • Loading Options
  • Changed Data Capture (CDC) and Publishing
  • Staging Areas

DIMENSIONAL MODELLING DEVELOPMENT LIFE CYCLE

  • Requirements Analysis
  • Requirements Gathering
  • Requirements Validation
  • Requirements Modeling
  • Schema Design
  • Project Definition
  • Warehouse Design
  • Implementation
  • Follow-up and Review

DIMENSIONAL MODLEING DESIGN

DATA CLEANING AND CONFORMING

  • Data Quality Criteria
  • Design Methods and Alternatives
  • Cleaning deliverables
  • Conforming Dimensions
  • Conforming Facts

DIMENSION TABLE DELIVERY

SLOWLY CHANGING DIMENSIONS (SCD)

SLOWLY CHANGING FACTS (SCF)

MULTIVALUED DIMENSIONS

  • Definition
  • Bridge Tables

FACT TABLE DELIVERY

FACT TABLE LOAD CONSIDERATIONS

  • Index Management
  • Partition Management
  • Updates, Deletes and Inserts
  • Recovery
  • Summary Tables
  • Parallelism

DATA WAREHOUSE PERFORMANCE DESIGN

  • Materialized View
  • Large Concurrent Reports
  • Short Running Queries
  • Long Running Queries
  • Random Queries
  • Occasional updates
  • On-Line utilities
  • Index Options
  • Partitioning and Parallelism

INTRODUCTION TO STATISTICS, ANALYTIC AND OLAP SQL QUERIES

GENERAL CONCEPTS
References:

 

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