Analysts Must Approach these Books to Handle the Big Data in Businesses

By POOJA BISHT |Email | Jun 4, 2019 | 7530 Views

Handling Big Data is the major priority of businesses today. In this article, we will go through 5 such amazing books to handle big data. 

The book is a comprehensive book discussing the success stories of the 45 companies of how they make sense of their big data and created huge revenues for the organization.
You will learn in the book:
  1. How predictive analytics helps Amazon, Target, John Deere and Apple understand their customers
  2. How big data is behind the success of Walmart, LinkedIn, Microsoft and more
  3. How big data is changing medicine, law enforcement, hospitality, fashion, science, and banking
  4. To develop your own big data strategy by accessing additional reading materials at the end of each chapter

The book will provide you a step-by-step approach to build your own big data strategy. The reader is provided with the most useful concepts in building a big data strategy with numerous real-world examples from a cross-section of companies and organizations. 
Key concepts discussed in the book:
  1. How companies need to clearly define what it is they need to know
  2. How companies can collect relevant data and measure the metrics that will help them answer their most important business questions
  3. How the results of big data analytics can be visualized and communicated to ensure key decision-makers understand them
This book examines the pros and cons of various technologies for processing and storing data. The book deals with the fundamental principles which are required by software engineers and architects to learn to make full use of data in modern applications. Difficult issues such as scalability, consistency, reliability, efficiency, and maintainability which are needed to be figured out are provided in the book. 
The learning that you will gain from the book are:
  1. How to use and operate the existing software you are using more effectively.
  2. To make informed decisions by identifying the strengths and weaknesses of different tools
  3. The distributed systems research upon which modern databases are built.

While there have been many technologies developed to handle big data, it is very difficult to handle geospatial data efficiently. It has always been a major challenge in geoinformatics to handle geospatial data as geospatial data come in various types and formats, and the databases involved are inherently very large. Big Data: Techniques and Technologies in Geoinformatics solve all these major challenges and provide the techniques and technologies to store, manage and compute geospatial data.
Various geospatial applications that fall under the category of big data are taught in the book to provide the learners the in-depth knowledge to handle it. All the technologies, and tools that are needed to collect, analyze, manage, process, and visualize geospatial big data are provided in the book.

The book teaches you how to build big data systems using an architecture that takes advantage of clustered hardware to analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. The book presents a realistic approach, and guides its readers through the theory of big data systems and to implement them in practice.
Key concepts discussed in the book are:
  1. Introduction to big data systems
  2. Real-time processing of web-scale data
  3. Big Data Tools like Hadoop, Cassandra, and Storm
  4. Extensions to traditional database skills.

Source: HOB