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Big Data Analytics Tutorial

The process of identifying, procuring, preparing, and analyzing large amounts of raw, unstructured data in order to extract meaningful information that can be used as an input for identifying patterns, enriching existing enterprise data, and performing large-scale searches is known as Big Data analytics.

Big data analytics is the use of advanced analytic techniques against very large, diverse data sets that include structured, semi-structured and unstructured data, from different sources, and in different sizes from terabytes to zettabytes.

Big Data Analytics Index

1. Fundamentals of Big Data Analytics
2. Hadoop Ecosystem and Its Components
3. What is Hadoop in Big Data? Components of Hadoop
4. What Is Descriptive Analytics? Procedure For Using
5. What Is Prescriptive Analytics? Advantages & Disadvantages
6. Big Data Analytics – Big Data Stack
7. What Is Predictive Analytics? Why It Is Important
8. Big Data Analytics – 7 V's of Big Data
9. Big Data Architecture - Detailed Explanation & Components
10. What Is Hypervisor? Detailed Explanation With Types
11. What is an Operational Database? Functions, Advantages & Disadvantages
12. What is key-value database? Explained with Examples
13. Big Data Types, Their Advantages and Disadvantages
14. Big Data Adoption and Planning Considerations
15. Data Abstraction in Big Data Analytics
16. Big Data Analytics Life Cycle
17. Top 15 Challenges of Big Data Analytics: An Overview
18. MapReduce in Big Data Analytics: Introduction and Origin
19. How MapReduce Works?
20. HDFS Architecture
21. Hadoop YARN Architecture: Explained with Features Key Components
22. Getting Started with Data Analytics using AWS Glue
23. Apache Kafka: Its Components, Messaging System, API's

Practice

• Big Data Analytics MCQs

Audience

This Big Data Analytics tutorial is helpful for the students as well as software professionals aspiring to learn the basics of Big Data Analytics.

Prerequisites

Before you start this Big Data Analytics Tutorial, you may have knowledge of databases, SQL, data warehousing/data processing, basic programming language, mathematics, and statistics.

Discuss

If you have any questions related to any topic of the Big Data Analytics Tutorial, you may ask in the comment section. Every topic has a comment section at the end of the page.