Practical Big Data Analytics
Nataraj Dasgupta
Sold by PBShop.store US, Wood Dale, IL, U.S.A.
AbeBooks Seller since 7 April 2005
New - Soft cover
Condition: New
Ships within U.S.A.
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Add to basketSold by PBShop.store US, Wood Dale, IL, U.S.A.
AbeBooks Seller since 7 April 2005
Condition: New
Quantity: 1 available
Add to basketNew Book. Shipped from UK. Established seller since 2000.
Seller Inventory # GB-9781783554393
Get command of your organizational Big Data using the power of data science and analytics
Key Features
Book Description
Big Data analytics relates to the strategies used by organizations to collect, organize, and analyze large amounts of data to uncover valuable business insights that cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization's data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages, and BI tools, selecting the right combination of technologies is an even greater challenge.
This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology and the practical reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB, and even learn how to write R code for neural networks.
By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using the different tools and methods articulated
in this book.
What you will learn
Who this book is for:
The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience.
"About this title" may belong to another edition of this title.
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