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Exploratory Data Mining and Data Cleaning

Book Hero Magic crafted this summary to help describe this book. While it's new and still learning, it may not be perfect - your feedback is welcome! Summary
Exploratory Data Mining and Data Cleaning by Tamraparni Dasu and Theodore Johnson dives into the complexities of handling and interpreting vast datasets in the computing and technology field. The book guides readers through methods for investigating data patterns and ensuring accuracy by employing effective data cleaning techniques. It provides practical insights and strategies for making sense of imperfect data and utilising it effectively for informed decision-making.
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Format: Hardback
$41100

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Book Hero Magic created this recommendation. While it's new and still learning, it may not be perfect - your feedback is welcome! IS THIS YOUR NEXT READ?

You might enjoy this book if you're keen on enhancing your skills in computational methods for cleaning and analysing complex data. It offers practical techniques and insights into solving data quality issues, which can be highly valuable for data scientists, analysts, or anyone involved in large-scale data projects. Perfect for those who appreciate a blend of theoretical concepts with actionable solutions.

Book Hero thinking about your next read

Many current books on data mining and analysis focus on the last stage of the analysis process (getting the results) and spend little time on the data exploration and data cleaning processes. The true challenge in data mining is creating a set that contains relevant and accurate information and determining the appropriate analysis techniques.

Book Hero Magic formatted this description to make it easier to read. While it's new and still learning, it may not be perfect - your feedback is welcome! Description

Exploratory Data Mining and Data Cleaning is written for practitioners of data mining, data cleaning, and database management. The book presents a technical treatment of data quality, including process, metrics, tools, and algorithms.

Focusing on developing an evolving modelling strategy through an iterative data exploration loop and incorporation of domain knowledge, the book addresses methods of detecting, quantifying, and correcting data quality issues that can significantly impact findings and decisions. It explores the use of commercially available tools alongside new algorithmic approaches.

Case studies are utilised to illustrate applications in real-life scenarios. The book also 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 analyse large amounts of unfamiliar data, managers of operations databases, and students in undergraduate or graduate level courses dealing with large-scale data analysis and data mining.

Series: Wiley Series in Probability and Statistics

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Book Hero Magic summarised reviews for this book. While it's new and still learning, it may not be perfect - your feedback is welcome! HOW HAS THIS BEEN REVIEWED?

Exploratory Data Mining and Data Cleaning by Tamraparni Dasu and Theodore Johnson is praised for incorporating multiple methods for data exploration and cleaning. Reviewers highlight its value for statisticians and data analysts seeking an integrated approach to improve data quality and conduct significant research in the field.

Book Hero reading reviews

Book Details

INFORMATION

ISBN: 9780471268512

Publisher: John Wiley & Sons Inc

Format: Hardback

Date Published: 10 June 2003

Country: United States

Imprint: Wiley-Interscience

Illustration: Charts: 14 B&W, 0 Color; Tables: 2 B&W, 0 Color; Graphs: 38 B&W, 0 Color

Audience: Professional and scholarly

DIMENSIONS

Spine width: 21.0mm

Width: 162.0mm

Height: 245.0mm

Weight: 515g

Pages: 224

About the Author

TAMRAPARNI DASU, PhD, and THEODORE JOHNSON, PhD, are both members of the technical staff at AT&T Labs-Research in Florham Park, New Jersey.

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