ETL and Data Warehousing: Fundamentals of Extract, Transform, Load

ETL and Data Warehousing: Fundamentals of Extract, Transform, Load
ETL and Data Warehousing: Fundamentals of Extract, Transform, Load by editor William Mitchell, with over 15 year experience in the field of Data Warehousing. This ETL reference manual is perfect for Developer, Project Manager, and Manager alike, providing a collection of key concepts for Data Extract, Transform and Load in the context of Warehousing. Here in one volume are the fundamentals of Data Movement with a comprehensive overview of Data Extraction and Data Transformation. Database concepts of Facts and Dimensions and the Relation Model are covered, along with warehousing concepts of Data Integration and Operational Data Stores. Chapters provide information on Data Profiling, Data Integrity, and Data Quality.
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“In computing, Extract, Transform and Load (ETL) refers to a process in database usage and especially in data warehousing that:

Extracts data from homogeneous or heterogeneous data sources
Transforms the data for storing it in proper format or structure for querying and analysis purpose
Loads it into the final target (database, more specifically, operational data store, data mart, or data warehouse)

Usually all the three phases execute in parallel since the data extraction takes time, so while the data is being pulled another transformation process executes, processing the already received data and prepares the data for loading and as soon as there is some data ready to be loaded into the target, the data loading kicks off without waiting for the completion of the previous phases.

ETL systems commonly integrate data from multiple applications(systems), typically developed and supported by different vendors or hosted on separate computer hardware. The disparate systems containing the original data are frequently managed and operated by different employees. For example a cost accounting system may combine data from payroll, sales and purchasing.”

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