Big Data Analytics: A Guide to Data Science Practitioners Making the Transition to Big Data

This book provides a comprehensive guide to Big Data Analytics,covering econometric and machine learning techniques with R and SQL. It includes code examples and tutorials for practical applications,using real datasets from empirical research. It helps data science practitioners navigate the transition to Big Data and gain insights from large data sets in business, economics, and the social sciences.

Format: Paperback / softback
Length: 310 pages
Publication date: 04 September 2023
Publisher: Taylor & Francis Ltd

Successfully navigating the data-driven economy requires a deep understanding of the technologies and methods used to extract valuable insights from Big Data. This comprehensive book is designed to assist data science practitioners in successfully transitioning to the realm of Big Data.

Building upon familiar content from applied econometrics and business analytics, this book introduces the reader to the fundamental concepts of Big Data Analytics. The primary focus of the book lies in teaching readers how to effectively employ econometric and machine learning techniques on large and complex data sets, as well as the various pre-analysis steps involved (such as data storage, data import, and data preparation).

The book seamlessly blends conceptual and theoretical material with practical applications of the concepts using the powerful programming languages R and SQL. By the end of the book, readers will possess the skills necessary to analyze large data sets, both locally and in the cloud. Numerous code examples and tutorials, specifically tailored for empirical economic and business research, serve as practical guides to handling and analyzing Big Data.

Key Features:
- Numerous code examples in R and SQL, with R/SQL scripts freely available online.
- Extensive use of real datasets from empirical economic research and business analytics, with data files freely provided online.
- Encourages readers to think critically about the bottlenecks encountered in practical data analysis tasks involving large data sets and provides strategies for addressing them.

This book is an invaluable resource for data science practitioners, graduate students, and researchers seeking to leverage the power of Big Data to address research questions in business, economics, and the social sciences.

Weight: 692g
Dimension: 178 x 254 x 18 (mm)
ISBN-13: 9781032458144