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Amazon Top 20 Books in Databases & Big Data


These are the most popular database & big data books on Amazon. Some interesting options here, so hopefully you find something useful to your current requirements.



By Matthew Mayo.

The recent explosion of interest in data science, data mining, big data, and related disciplines has been mirrored by an explosion in book titles on these same topics. One of the best ways to decide which books could be useful for your career is to look at which books others are reading.

This post details the 20 most popular titles in Amazon's Databases and Big Data Books category as of Nov 15, 2015.

Note: KDnuggets gets absolutely no royalties from Amazon - this list is presented only to help our readers evaluate interesting books.

Amazon Database Books

1. Data Science From Scratch: First Principles with Python
by Joel Grus
4.3 out of 5 stars (38 reviews)
Paperback, $28.51

2. Not Applicable (that book was not actually relevant to Databases / Big Data).

3. Not Applicable.

4. Data Smart: Using Data Science to Transform Information into Insight
by John W. Foreman
4.8 out of 5 stars (83 reviews)
Paperback, $27.48

5. Not Applicable.

6. Data Science for Business: What You Need to Know About Data Mining and Data-Analytic Thinking
by Foster Provost & Tom Fawcett
4.6 out of 5 stars (122 reviews)
Paperback, $37.99

7. Not Applicable.

8. SQL in 10 Minutes, Sams Teach Yourself
by Ben Forta
4.5 out of 5 stars (302 reviews)
Paperback, $22.22

9. Data Analytics Made Accessible
by Anil Maheshwari
4.8 out of 5 stars (77 reviews)
Kindle, $7.50

10. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
by Wes McKinney
4.2 out of 5 stars (105 reviews)
Paperback, $27.68

11. The Elements of Statistical Learning: Data Mining, Inference, and Prediction
by Trevor Hastie, Robert Tibshirani & Jerome Friedman
4.2 out of 5 stars (58 reviews)
Hardcover, $65.91

12. Python Machine Learning
by Sebastian Raschka
4.9 out of 5 stars (11 reviews)
Paperback, $40.21

13. Data Science from Scratch: First Principles with Python
by Joel Grus
4.3 out of 5 stars (38 reviews)
Kindle, $23.41

14. Learning Spark: Lightning-Fast Big Data Analysis
by Holden Karau, Andy Konwinski, Patrick Wendell & Matei Zaharia
4.2 out of 5 stars (33 reviews)
Paperback, $36.26

15. Data Smart: Using Data Science to Transform Information into Insight
by John W. Foreman
4.8 out of 5 stars (83 stars)
Kindle, $27.01

16. Data Science for Business: What You Need to Know About Data Mining and Data-Analytic Thinking
by Foster Provost & Tom Fawcett
4.6 out of 5 stars (122 reviews)
Kindle, $14.85

17. Not Applicable.

18. Show Me the Numbers: Designing Tables and Graphs to Enlighten
by Stephen Few
4.6 out of 5 stars (36 reviews)
Hardcover, $26.55

19. Amazon Web Services in Action
by Andreas Wittig & Michael Wittig
5.0 out of 5 stars (1 review)
Paperback, $38.40

20. Not Applicable.

21. SQL: Learn SQL In A DAY!
by Acodemy
4.8 out of 5 stars (25 reviews)
Kindle, $3.00

22. Big Data: Principles and best practices of scalable realtime data systems
by Nathan Marz & James Warren
4.5 out of 5 stars (21 reviews)
Paperback, $29.58

23. Not Applicable.

24. Not Applicable.

25. Training Kit (Exam 70-461) Querying Microsoft SQL Server 2012 (MCSA)
by Dejan Sarka, Itzik Ben-Gan & Ron Talmage
4.1 out of 5 (145 reviews)
Paperback, $44.03

26. Not Applicable.

27. Tableau 9: The Official Guide
by George Peck
5.0 out of 5 (2 reviews)
Paperback, $34.81

28. Python Machine Learning
by Sebastian Raschka
4.9 out of 5 stars (11 reviews)
Kindle, $27.01

29. Access 2013 Bible
by Michael Alexander & Richard Kusleika
4.2 out of 5 stars (75 reviews)
Paperback, $30.84

Bio: Matthew Mayo is a computer science graduate student currently working on his thesis parallelizing machine learning algorithms. He is also a student of data mining, a data enthusiast, and an aspiring machine learning scientist.

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