Big Data Analytics Tutorial

In this guide, we will walk you through the core concepts, tools and practical applications of Big Data Analytics, starting from the basics to advanced topics. By the end of this tutorial, you'll have a strong foundation in Big Data and tools like Hadoop, Hive, Pig and Spark.

Big Data Analytics involves examining large and complex data sets to uncover hidden patterns, correlations and trends. Industries use it to drive decisions based on data insights.

What is Big Data?

In this section, we will explore what Big Data means and how it differs from traditional data. Big Data is characterized by its large volume, high velocity and diverse variety making it difficult to process with traditional tools.

• What is Big Data?
• What is Unstructured Data?
• What is Semi-Structured Data?
• 6V's of Big Data
• What is Distributed Computing?

What is Hadoop ?

Hadoop is an open-source framework written in Java that allows distributed storage and processing of large datasets. Before Hadoop, traditional systems were limited to processing structured data mainly using RDBMS and couldn't handle the complexities of Big Data. In this section we will learn how Hadoop offers a solution to handle Big Data.

• Hadoop - Introduction
• Hadoop Architecture
• Hadoop 2.x vs Hadoop 3.x
• Hadoop - Ecosystem

Refer this article for learning more on this topic: Hadoop Tutorial

What is MapReduce?

MapReduce is a programming model that allows parallel processing of large datasets. It divides a task into smaller managable tasks that can be processed across multiple machines. In this section we will learn about MapReduce and its components.

• Map Reduce in Hadoop
• MapReduce Architecture
• Mapper In MapReduce
• Reducer in Map-Reduce

What is Hive?

Hive is a data warehouse system built on top of Hadoop that allows querying and managing large datasets using a SQL-like language.

• Apache Hive
• Apache HIVE - Database Options
• Apache HIVE - Features And Limitations
• Apache Hive - Getting Started With HQL Database Creation And Drop Database

What is Apache Pig?

Pig is a high-level platform used for creating MapReduce programs used with Hadoop. It simplifies data processing tasks through its own scripting language, Pig Latin.

• Introduction to Apache Pig
• Difference between MapReduce and Pig
• Difference between Pig and Hive

Introduction to Machine Learning with Big Data

Big Data Analytics also integrates with Machine Learning to build predictive models. Here we do:

• Build and train machine learning models using large datasets.
• Use libraries like MLlib (for Spark) to implement machine learning algorithms.

To know more about machine learning refer to: Machine Learning Tutorial

Big Data Analytics is a skill that enables professionals to make data-driven decisions by analyzing large datasets. By learning tools like Hadoop, Hive and Pig and applying them in real-world projects, you can unlock valuable insights for businesses and organizations.