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)

Importance and implications of streaming data

Data is valuable in all organizations. Streaming data, unlike other data, holds all the truth, and this data processing is profitable in most scenarios. In this section, we are going to explore the importance and implications of streaming data.

Needs for stream processing

Big data has proved to derive insights from the data that has been successfully used in business intelligence and the enhancement of the existing system. Some of these insights have much higher values shortly after it has occurred. Stream processing targets such scenarios. The following are some of the reasons to use stream processing:

  • There is a never-ending stream of events occurring in real life. Streaming...