Ulrich Matter

Big Data Analytics (eBook, PDF)

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

• Format: PDF

Produktbeschreibung

Successfully navigating the data-driven economy presupposes a certain understanding of the technologies and methods to gain insights from Big Data. This book aims to help data science practitioners to successfully manage the transition to Big Data.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 328
• Erscheinungstermin: 4. September 2023
• Englisch
• ISBN-13: 9781000932720
• Artikelnr.: 68334311

Autorenporträt

Ulrich Matter is an Assistant Professor of Economics at the University of St.Gallen. His primary research interests lie at the intersection of data science, political economics, and media economics. His teaching activities cover topics in data science, applied econometrics, and data analytics. Before joining the University of St. Gallen, he was a Visiting Researcher at the Berkman Klein Center for Internet & Society at Harvard University and a postdoctoral researcher and lecturer at the Faculty for Business and Economics, University of Basel.

Inhaltsangabe

Part 1. Setting the Scene: Analyzing Big Data 1. What is Big in "Big Data"?
2. Approaches to Analyzing Big Data 3. The Two Domains of Big Data
Analytics Part 2. Platform: Software and Computing Resources 4. Software:
Programming with (Big) Data 5. Hardware: Computing Resources 6. Distributed
Systems 7. Cloud Computing Part 3. Components of Big Data Analytics 8. Data
Collection and Data Storage 9. Big Data Cleaning and Transformation 10.
Descriptive Statistics and Aggregation 11. (Big) Data Visualization Part 4.
Application: Topics in Big Data Econometrics 12. Bottlenecks in Everyday
Data Analytics Tasks 13. Econometrics with GPUs 14. Regression Analysis and
Categorization with Spark and R 15. Large-scale Text Analysis with sparklyr
Part 5. Appendices Appendix A. GitHub Appendix B. R Basics Appendix C.
Install Hadoop