Big Data; as its name implies, the data which is bigger is known as big data. The data size is increasing day by day. An individual deals with data using mobile phones, tabs, and laptops while an organisation deals with business data; statistically it has been noted that the data size has drastically increased in the past decade.

What is Big Data?

The term “Big Data” usually refers to datasets that are too large, complex and unable to be processed by ordinary data processing systems to manage efficiently. These datasets can be derived from a variety of sources, including social media, sensors, internet activity, and mobile devices. The data can be structured, semi-structured and unstructured type of data.

Big Data Analytics

A process of analysing large and diverse data sets is known as “Big Data,” It discovers hidden patterns, unknown relationships, market trends, user preferences, and other important information. It uses advanced analytics techniques such as statistical analysis, machine learning, data mining, and predictive modelling to extract insights from enormous datasets.

Organisations across the world capture terabytes of data about their users” interactions, business, social media, and also sensors from devices such as mobile phones and automobiles. The challenge of this era is to make sense of this sea of data. This is where big data analytics comes into the picture.

Where Big Data Analytics Used?

Big Data Analytics strives to assist organisations in making more informed business decisions, increasing operational efficiency, improving customer experiences and services, and making sure to sustain industries in a competitive world with their respective industries. The Big Data Analytics process involves data gathering, storage, processing, analysis, and visualisation of outcomes to make strategic business decisions. The process of converting large amounts of unstructured raw data, retrieved from different sources to a data product useful for organizations forms the core of Big Data Analytics.

Overall, Big Data Analytics enables organizations to harness the vast amounts of data available to them and turn it into actionable insights that drive business growth and innovation.

In this big data analytics tutorial, we will discuss the most fundamental concepts and methods of Big Data Analytics.

Audience

This tutorial has been prepared for software professionals aspiring to learn the basics of Big Data Analytics. Professionals who are into analytics, in general, may as well use this tutorial to good effect.

Prerequisites

Before you start proceeding with this tutorial, we assume that you have prior exposure to handling huge volumes of unprocessed data at an organizational level.

Through this tutorial, we will develop a mini project to provide exposure to a real-world problem and how to solve it using Big Data Analytics.