Data Analytics: Principles, Tools, and Practices

A Complete Data Analytics Guide for Learners and Professionals.

KEY FEATURES  

• Learn Big Data, Hadoop Architecture, HBase, Hive and NoSQL Database.
• Dive into Machine Learning, its tools, and applications.
• Coverage of applications of Big Data, Data Analysis, and Business Intelligence.

DESCRIPTION 

These days critical problem solving related to data and data sciences is in demand. Professionals who can solve real data science problems using data science tools are in demand. The book “Data Analytics: Principles, Tools, and Practices” can be considered a handbook or a guide for professionals who want to start their journey in the field of data science. 

The journey starts with the introduction of DBMS, RDBMS, NoSQL, and DocumentDB. The book introduces the essentials of data science and the modern ecosystem, including the important steps such as data ingestion, data munging, and visualization. The book covers the different types of analysis, different Hadoop ecosystem tools like Apache Spark, Apache Hive, R, MapReduce, and NoSQL Database. It also includes the different machine learning techniques that are useful for data analytics and how to visualize data with different graphs and charts. The book discusses useful tools and approaches for data analytics, supported by concrete code examples. 

After reading this book, you will be motivated to explore real data analytics and make use of the acquired knowledge on databases, BI/DW, data visualization, Big Data tools, and statistical science.

WHAT YOU WILL LEARN

• Familiarize yourself with Apache Spark, Apache Hive, R, MapReduce, and NoSQL Database.
• Learn to manage data warehousing with real time transaction processing.
• Explore various machine learning techniques that apply to data analytics.
• Learn how to visualize data using a variety of graphs and charts using real-world examples from the industry.
• Acquaint yourself with Big Data tools and statistical techniques for machine learning.

WHO THIS BOOK IS FOR

IT graduates, data engineers and entry-level professionals who have a basic understanding of the tools and techniques but want to learn more about how they fit into a broader context are encouraged to read this book.

1. Database Management System
2. Online Transaction Processing and Data Warehouse
3. Business Intelligence and its deeper dynamics
4. Introduction to Data Visualization
5. Advanced Data Visualization
6. Introduction to Big Data and Hadoop
7. Application of Big Data Real Use Cases
8. Application of Big Data
9. Introduction to Machine Learning
10. Advanced Concepts to Machine Learning
11. Application of Machine Learning

Gaurav Aroraa is a technology enthusiast with a Doctorate in Computer Science. He is a Microsoft MVP award recipient. He is a lifetime member of the Computer Society of India (CSI), an advisory member and a senior mentor at IndiaMentor, certified as a Scrum trainer and coach, ITIL-F certified, and PRINCE-F and PRINCE-P certified. He is an open-source developer and a contributor to the Microsoft TechNet community. He has authored books across-the-technologies, including Microservices by Examples Using .NET Core (BPB).

LinkedIn Profile: Gaurav Aroraa

Blog Link: http://gaurav-arora.com/blog/ 

Chitra Lele is a young software engineer, software solution architect, record-setting author, award-winning poet, and research scholar. She is a merit-holder and holds degrees in Software Engineering and Computer Management. She runs her software startup firm, Chitra Lele & Associates, which designs software solutions based on Ethically-Aligned Design principles. She is also the founder of ‘Chitra Cares’, a social transformation initiative dedicated to community building projects.  Through her software projects, peace work, academic books, and social transformation initiatives, she strives to contribute to the greater good of the world.

LinkedIn Profile: Chitra Lele 

Blog Link: https://chitracares.com/