Data Analytics: Principles, Tools, and Practices: A Complete Guide for Advanced Data Analytics Using the Latest Trends, Tools, and Technologies
暫譯: 數據分析：原則、工具與實踐：高級數據分析的完整指南，使用最新趨勢、工具與技術

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.

TABLE OF CONTENTS

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