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

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:

How predictive analytics helps Amazon, Target, John Deere and Apple understand their customers
How big data is behind the success of Walmart, LinkedIn, Microsoft and more
How big data is changing medicine, law enforcement, hospitality, fashion, science, and banking
To develop your own big data strategy by accessing additional reading materials at the end of each chapter

Big Data - Using SMART Big Data, Analytics and Metrics To Make Better Decisions and Improve Performance

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:

How companies need to clearly define what it is they need to know
How companies can collect relevant data and measure the metrics that will help them answer their most important business questions
How the results of big data analytics can be visualized and communicated to ensure key decision-makers understand them

Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems

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:

How to use and operate the existing software you are using more effectively.
To make informed decisions by identifying the strengths and weaknesses of different tools
The distributed systems research upon which modern databases are built.

Big Data: Techniques and Technologies in Geoinformatics

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.

Big Data: Principles and best practices of scalable realtime data systems

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:

Introduction to big data systems
Real-time processing of web-scale data
Big Data Tools like Hadoop, Cassandra, and Storm
Extensions to traditional database skills.

Source: HOB

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