Big Database Tutorial

Big Data provides volume, velocity, variety and veracity to large data.

Big Databases Tutorial

Learn the concepts of Big Database with this complete Big Databases Tutorial. Useful for beginners, this tutorial discusses the basic and advance concepts and techniques of Big Databases with examples. Freshers, BE, BTech, MCA, college students will find it useful to develop notes, for exam preparation, solve lab questions, assignments and viva questions.

Who is this Big Databases Tutorial designed for?

This tutorial is especially useful for beginners wanting to learn Big Databases for their studies and exams.

What do I need to know to begin with?

To start learning Big Databases, you should have a good knowledge of database and data warehousing concepts.

Big Databases syllabus covered in this tutorial

Introduction to Big Database, NoSQL Databases, Cassandra, Architecture of Cassandra, Cassandra Query Language etc.

Introduction

  • With an ever increasing growth of databases in activities like social networking, online shopping, e-learning, e-banking etc; managing such a huge amount of data is  very big challenge.
  • The traditional data management systems and other existing tools are facing difficulties to analyze and process such a big data.
  • 'Big Data' means a collection of the structured and unstructured data which is large and difficult to analyze and process with traditional data management system.

Four Vs of Big Data

Big data provides some important parameters for data processing. They are:

1. Volume:
It refers to the generation of large amount of data during data processing by using an application at every moment.
For example: Twitter Messages

2. Velocity:
It refers to the speed at which new data is generated and the speed at which data moves around the globe.
For example: Stock Exchange.

3. Variety:
It refers to the different types of data which are used in processing. The data can be structured or unstructured.
For example: In face-book, user can share data in the form of text, audio, video.

4. Veracity:
It refers to the trustworthiness of the data, Reliability data is important for organizations as well as users.
For example:  Twitter post with abbreviations.
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