Exploratory Data Mining and Data Cleaning
- Written for practitioners of data mining, data cleaning and database management.
- Presents a technical treatment of data quality including process, metrics, tools and algorithms.
- Focuses on developing an evolving modeling strategy through an iterative data exploration loop and incorporation of domain knowledge.
- Addresses methods of detecting, quantifying and correcting data quality issues that can have a significant impact on findings and decisions, using commercially available tools as well as new algorithmic approaches.
- Uses case studies to illustrate applications in real life scenarios.
- Highlights new approaches and methodologies, such as the DataSphere space partitioning and summary based analysis techniques.
Exploratory Data Mining and Data Cleaning will serve as an important reference for serious data analysts who need to analyze large amounts of unfamiliar data, managers of operations databases, and students in undergraduate or graduate level courses dealing with large scale data analys is and data mining.
226 pages; ISBN 9780471458647
, or download in
Title: Exploratory Data Mining and Data Cleaning
Author: Tamraparni Dasu; Theodore Johnson
Hadoop: The Definitive Guide 2012 US$ 39.99 688 pages
Alan Turing: The Enigma 2014 US$ 16.95 777 pages
- Academic > Mathematics > General > Mathematics
- Academic > Computer Science > Computer science
- Academic > Computer Science > Electronic data processing
- Academic > Computer Science > Computers - special aspects
- Academic > Computer Science > System design; Periodicals
- Academic > Computer Science > Database management
- Academic > Computer Science > Data mining
- Academic > Mathematics > Instruments and machines
- Academic > Mathematics > Geometry. Trigonometry.Topology
- Computers > Database Management > Data Mining
- Computers > Networking
- Computers > Data Processing
- Computers > Artificial Intelligence