Ebook Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data
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Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data
Ebook Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data
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From the Back Cover
Data Science and Big Data Analytics Discovering, Analyzing, Visualizing and Presenting Data Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities, methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are relevant to any industry and technology environment, and the learning is supported and explained with illustrative examples 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 analyze big data Learn how to tell a compelling story with data to drive business action Prepare for EMC ProvenTM Professional Data Scientist certification EMC Proven™ Professional is a leading education and certification program in the IT industry, providing comprehensive coverage of information storage technologies, virtualization, cloud computing, data science/big data analytics, and more... Being Proven means investing in yourself and formally validating your expertise! This book prepares you for the Data Science Associate exam E20-007 leading to EMC Proven Professional Data Science Associate (EMCDSA) certification. Visit http://education.EMC.com for details.
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About the Author
EMC is a global leader in enabling businesses and service providers to transform their operations and deliver IT as a service. Fundamental to this transformation is cloud computing. Through innovative products and services, EMC accelerates the journey to cloud computing, helping IT departments to store, manage, protect and analyze their most valuable asset — information — in a more agile, trusted and cost-efficient way. Additional information about EMC can be found at www.EMC.com
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Product details
Hardcover: 432 pages
Publisher: Wiley; 1 edition (January 27, 2015)
Language: English
ISBN-10: 111887613X
ISBN-13: 978-1118876138
Product Dimensions:
7.3 x 1.2 x 9.3 inches
Shipping Weight: 2.6 pounds (View shipping rates and policies)
Average Customer Review:
3.9 out of 5 stars
21 customer reviews
Amazon Best Sellers Rank:
#115,317 in Books (See Top 100 in Books)
Great book. I purchased to study for the Dell EMC DECA-DS certification, formerly “EMCDSAâ€. The book uses mostly R code examples which are great and understandable, but it did require me learning a little bit of R to fully comprehend. I come from a Python background and would have preferred more Python examples. There is very little Python based examples, mostly just for text mining. The book does get into Hadoop and related tools, but really at more of a theoretical level or basic overview.
Good but this stuff gets depricated so quickly unless this books gets updated every six months it is better to follow online courses and material. Most basic stuff of course still holds but rest is outdated.
I like this book
One of the best entry level books on big data analytics.
Excellent book for completing the Data Science and Big Data Analytics Dell EMC Proven Professional Course. It is an excellent reference for any Data Analytics project
This book is a great one. I found it easy to read.
This is a pretty decent book that covers a broad spectrum of topics including the the analytics life cycle, a brief but concise intro to R, to covering most of the advanced methods for analysis (k-means, linear regression, Naive Bayes, etc). It doesn't shy away from the math - but doesn't overwhelm either and, for the most part, is a fairly easy read. It should be treated as a reference and as a guide for the EMCDSA (EMC Data Science Associate) certification. There are probably better books for those just wading into data science but definitely worth adding to your library. For those who are complaining about no companion code examples it was an easy download from the Wiley website.
Excellent book. I have used it for teaching a graduate course in Analytics. I wish there were more examples on big data.
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