Etl Techniques for Data Warehousing The Complete Guide to Extract, Transform, and Load Techniques

Most every Fortune 5000 company runs one or more data warehouses to track customers and sales; their investment in maintaining these data warehouses runs into the billions of dollars. In the current IT climate, companies are looking for ways to use this investment more efficiently. For example, Wal-Mart found that its data bases stored huge volumes of obsolete and rarely used data; eliminating this data saved millions of dollars in maintenance costs and provided room to grow without having to invest in new equipment. The Wal-Mart story is a common one; the way to prevent it is the subject of this book. Extract, Transform, and Load (ETL) refers to the process in which data is extracted from source databases throughout the enterprise, transformed into a common format, cleansed of redundant and unneeded data, and then loaded into a data warehouse. ETL is the single most important step in building a data warehouse, consuming nearly 750f the total time and effort of building the warehouse; it also employs most of the developers on these projects. If ETL is done right, companies will maximize their use of storage; if not, they'll end up like Wal-Mart, wasting millions of dollars. "ETL Techniques for Data Warehousing" is expected to be the first book to show data warehouse developers how to master the ETL process. The book will be technically reviewed by Ralph Kimball, who is expected to endorse the book as well.Caserta, Joe is the author of 'Etl Techniques for Data Warehousing The Complete Guide to Extract, Transform, and Load Techniques' with ISBN 9780471446774 and ISBN 0471446777.