Data Wrangling
Concepts, Applications and Tools
- English
- PDF
- Available on iOS & Android
Data Wrangling
Concepts, Applications and Tools
About This Book
DATA WRANGLING
Written and edited by some of the world's top experts in the field, this exciting new volume provides state-of-the-art research and latest technological breakthroughs in data wrangling, its theoretical concepts, practical applications, and tools for solving everyday problems.
Data wrangling is the process of cleaning and unifying messy and complex data sets for easy access and analysis. This process typically includes manually converting and mapping data from one raw form into another format to allow for more convenient consumption and organization of the data. Data wrangling is increasingly ubiquitous at today's top firms.
Data cleaning focuses on removing inaccurate data from your data set whereas data wrangling focuses on transforming the data's format, typically by converting "raw" data into another format more suitable for use. Data wrangling is a necessary component of any business. Data wrangling solutions are specifically designed and architected to handle diverse, complex data at any scale, including many applications, such as Datameer, Infogix, Paxata, Talend, Tamr, TMMData, and Trifacta.
This book synthesizes the processes of data wrangling into a comprehensive overview, with a strong focus on recent and rapidly evolving agile analytic processes in data-driven enterprises, for businesses and other enterprises to use to find solutions for their everyday problems and practical applications. Whether for the veteran engineer, scientist, or other industry professional, this book is a must have for any library.
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Table of contents
- Cover
- Title Page
- Copyright Page
- Contents
- Chapter 1 Basic Principles of Data Wrangling
- Chapter 2 Skills and Responsibilities of Data Wrangler
- Chapter 3 Data Wrangling Dynamics
- Chapter 4 Essentials of Data Wrangling
- Chapter 5 Data Leakage and Data Wrangling in Machine Learning for Medical Treatment
- Chapter 6 Importance of Data Wrangling in Industry 4.0
- Chapter 7 Managing Data Structure in R
- Chapter 8 Dimension Reduction Techniques in Distributional Semantics: An Application Specific Review
- Chapter 9 Big Data Analytics in Real Time for Enterprise Applications to Produce Useful Intelligence
- Chapter 10 Generative Adversarial Networks: A Comprehensive Review
- Chapter 11 Analysis of Machine Learning Frameworks Used in Image Processing: A Review
- Chapter 12 Use and Application of Artificial Intelligence in Accounting and Finance: Benefits and Challenges
- Chapter 13 Obstacle Avoidance Simulation and Real-Time Lane Detection for AI-Based Self-Driving Car
- Chapter 14 Impact of Suppliers Network on SCM of Indian Auto Industry: A Case of Maruti Suzuki India Limited
- About the Editors
- Index
- EULA