Book Image

Hands-On Big Data Modeling

By : James Lee, Tao Wei, Suresh Kumar Mukhiya
Book Image

Hands-On Big Data Modeling

By: James Lee, Tao Wei, Suresh Kumar Mukhiya

Overview of this book

Modeling and managing data is a central focus of all big data projects. In fact, a database is considered to be effective only if you have a logical and sophisticated data model. This book will help you develop practical skills in modeling your own big data projects and improve the performance of analytical queries for your specific business requirements. To start with, you’ll get a quick introduction to big data and understand the different data modeling and data management platforms for big data. Then you’ll work with structured and semi-structured data with the help of real-life examples. Once you’ve got to grips with the basics, you’ll use the SQL Developer Data Modeler to create your own data models containing different file types such as CSV, XML, and JSON. You’ll also learn to create graph data models and explore data modeling with streaming data using real-world datasets. By the end of this book, you’ll be able to design and develop efficient data models for varying data sizes easily and efficiently.
Table of Contents (17 chapters)

Concept and Approaches of Big-Data Management

This chapter deals with exploring various database management system (DBMS) and non-DBMS-based approaches to big data. It also focuses on the benefits of using a DBMS over the traditional filesystem, differences between parallel and distributed filesystems, and the MapReduce-style DBMS. In this chapter, we will be learning about the following topics:

  • Various benefits of using a DBMS over the traditional filesystem
  • Differences between a parallel and distributed filesystem
  • MapReduce-style DBMS