Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data

by EMC Education Services

Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you:

Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Corresponding data sets are available at www.wiley.com/go/9781118876138.

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Genres: Nonfiction, Computer Science, Science

432 pages, Hardcover

First published November 3, 2014

Reviews

[Matt · Rating 4 out of 5]

A good, broad textbook on data analysis and presentation in R, with introductory modelling techniques including regression, classification, clustering, association rule mining, and time series methods. Together with An Introduction to Statistical Learning with Applications in R by James et al., I'd recommend it to anyone aspiring to do quantitative research, be it data science, business/finance/economics, etc.

[Zach · Rating 2 out of 5]

While this is a nice intro into machine learning in R, I think Hands-on Machine Learning with sklearn takes a much better approach (although it's in python). The code and data is accessible through github and there's an emphasis on theory rather than strictly formulas.

[David · Rating 4 out of 5]

Great overview and enough detail of analytics models. Just the book I was looking for to go little deeper on understanding the analytical models (for non-data scientist)