Big Data and Analytics The key concepts and practical applications of big data analytics (English Edition)
Free Download Big Data and Analytics: The key concepts and practical applications of big data analytics (English Edition) by Dr. Jugnesh Kumar, Dr. Anubhav Kumar, Dr. Rinku Kumar
English | March 5, 2024 | ISBN: 9355516177 | 232 pages | MOBI | 1.90 Mb
Unveiling insights, unleashing potential: Navigating the depths of big data and analytics for a data-driven tomorrow
Key Features
● Learn about big data and how it helps businesses innovate, grow, and make decisions efficiently.
● Learn about data collection, storage, processing, and analysis, along with tools and methods.
● Discover real-life examples of big data applications across industries, addressing challenges like privacy and security.
Description
Big data and analytics is an indispensable guide that navigates the complex data management and analysis. This comprehensive book covers the core principles, processes, and tools, ensuring readers grasp the essentials and progress to advanced applications.
It will help you understand the different analysis types like descriptive, predictive, and prescriptive. Learn about NoSQL databases and their benefits over SQL. The book centers on Hadoop, explaining its features, versions, and main components like HDFS (storage) and MapReduce (processing). Explore MapReduce and YARN for efficient data processing. Gain insights into MongoDB and Hive, popular tools in the big data landscape.
What you will learn
● Grasp big data fundamentals and applications.
● Master descriptive, predictive, and prescriptive analytics.
● Understand HDFS, MapReduce, YARN, and their functionalities.
● Explore data storage, retrieval, and manipulation in a NoSQL database.
● Gain practical insights and apply them to real-world scenarios.
Who this book is for
This book caters to a diverse audience, including data professionals, analysts, IT managers, and business intelligence practitioners.
Table of Contents
1. Introduction to Big Data
2. Big Data Analytics
3. Introduction of NoSQL
4. Introduction to Hadoop
5. Map Reduce
6. Introduction to MongoDB
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