Cowritten by Ralph Kimball, the world's leading data warehousing authority, whose previous books have sold more than 150,000 copiesDelivers real-world solutions for the most time- and labor-intensive portion of data warehousing-data staging, or the extract, transform, load (ETL) processDelineates be
The Data WarehouseETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data
โ Scribed by Ralph Kimball, Joe Caserta
- Publisher
- Wiley
- Year
- 2004
- Tongue
- English
- Leaves
- 526
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
- Cowritten by Ralph Kimball, the world's leading data warehousing authority, whose previous books have sold more than 150,000 copies
- Delivers real-world solutions for the most time- and labor-intensive portion of data warehousing-data staging, or the extract, transform, load (ETL) process
- Delineates best practices for extracting data from scattered sources, removing redundant and inaccurate data, transforming the remaining data into correctly formatted data structures, and then loading the end product into the data warehouse
- Offers proven time-saving ETL techniques, comprehensive guidance on building dimensional structures, and crucial advice on ensuring data quality
๐ SIMILAR VOLUMES
<p><b>Discover how to describe your data in detail, identify data issues, and find out how to solve them using commonly used techniques and tips and tricks</b></p><h4>Key Features</h4><ul><li>Get well-versed with various data cleaning techniques to reveal key insights</li><li>Manipulate data of diff
Discover how to describe your data in detail, identify data issues, and find out how to solve them using commonly used techniques and tips and tricks Key Features โข Get well-versed with various data cleaning techniques to reveal key insights โข Manipulate data of different complexities to shape
<p>Data cleaning is a waste of time.</p><p>If the data had been collected properly in the first place there wouldn't be any cleaning to do, and you wouldn't now be faced with the prospect of weeks of cleaning to get your dataset analysis-ready.</p><p>Worse still, your boss won't understand why your