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Chapter 19. Data Warehousing and Data Mining

Chapter 19. data Warehousing and data MiningTable of contents Objectives Context General introduction to data Warehousing What is a data warehouse? Operational systems vs. data Warehousing systems Operational systems data Warehousing systems Differences between operational and data Warehousing systems Benefits of data Warehousing systems data warehouse architecture Overall architecture The data warehouse data transformation Metadata Access tools Query and reporting tools Application development tools Executive information systems (EIS) tools OLAP data Mining tools data visualisation data marts Information delivery system data warehouse blueprint data architecture Volumetrics Transformation data cleansing data architecture requirements Application architecture Requirements of tools Technology architecture Star schema design Entities within a data warehouse Measure entities Dimension entities Category detail entities Translating information into a star schema data extraction and cleansing Extraction specifications Loading data Multiple passes of data1 Staging area Checkpoint restart logic data loading data Warehousing and data Mining General introduction to data mini

Data mining is a process of extracting information and patterns, which are pre-viously unknown, from large quantities of data using various techniques ranging from machine learning to statistical methods. Data could have been stored in files, Relational or OO databases, or data warehouses. In this chapter, we will

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