What Is Big Data Analytics and Why Is It So Important? | 4 Types of Big Data Analytics Explained

Описание: What is big data analytics? In this tutorial for beginners, we demonstrate how 4 types of big data analytics can be used to organize and analyze large sets of data with examples. Learn how data is collected, organized, and analyzed for faster decision-making. We'll also discuss how it helps with risk management and innovation.

00:00 - Intro
00:06 - What is big data analytics?
00:36 - Big data analytics description
00:46 - How big data analytics can be used for?
01:00 - 4 types of big data analytics
01:03 - Descriptive analytics
01:15 - Diagnostic analytics
01:27 - Predictive analytics
01:38 - Prescriptive analytics
01:47 - How big data analytics can help organizations?
02:00 - Big data analytics lifecycle

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Huge amount of data is created everyday by individuals, private companies and organizations. Social media applications, video platforms, call centers store vast amount of data.

Big Data Analytics is a trending concept that uses both technologies and mathematical developments in order to analyze behaviours of customers and trends on the market.

There are four types of Big Data Analytics
1. Descriptive Analytics
2. Diagnostic Analytics
3. Predictive Analytics
4. Prescriptive Analytics

Big Data Analytics Life Cycle
Unlike the previous approaches, today’s big data context is much more sophisticated. The below big data analytics life cycle phases constitute most of the work in a successful project.

Stage 1 – The evaluation of the Business case

Stage 2 – Data identification

Stage 3 – The Filtering of data

Stage 4 – The extraction of data

Stage 5 – The collection of data

Stage 6 – The analysis of data

Stage 7 – Data Visualization

Stage 8 – Final result analysis

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