Preface

The Hands-On Big Data Modelling series explores the methodology required to model big data using open source platforms in real-world contexts. The rapid growth of big data and people's interest in extracting business intelligence from data have given an opportunity to explore various technologies and methods that can be applied in modeling, mining, and analytics generation. In this book, we are going to use open source tools such as Python, R, Gephi, Lucene, and Weka to explore how big data modeling can be facilitated. The main objectives of this book are as follows:

• To understand the concept of big data, the sources of big data, and the importance and implications of big data and big data management
• To understand state-of-the-art big data modeling, the importance of big data modeling, big data applications, and programming platforms for big data analysis
• To encourage a range of discussion of concepts, from Database Management Systems (DBMSes) to Big Data Management Systems (BDMSes)
• To facilitate the planning, analysis, and construction of data models through an actual database for small to enterprise-level database environments
• To understand the concept of unified data models for structured, semi-structured, and unstructured data, including finding classes, adding attributes, and simplifying the data structures, followed by advanced data modeling techniques and performance scaling of models
• To facilitate working with streaming data with the help of examples on Twitter feeds and weather data points
• To understand how we can model using open access data such as Bitcoin, IMDB, Twitter, and weather data using Python