What is big data analytics?

Big Data is today, the hottest buzzword around, and with the amount of data being generated every minute by consumers, or/and businesses worldwide, there is huge value to be found in Big Data analytics.

The first we must understand What is Big Data?

So, What is Big Data?

Big Data is a massive amount of data sets that cannot be stored, processed, or analyzed using traditional tools. Big Data in its raw form is of no use. So, now let us understand Big Data Analytics.

Today, there are millions of data sources that generate data at a very rapid rate. These data sources are present across the world. Some of the largest sources of data are social media platforms and networks. Let’s use Facebook as an example—it generates more than 500 terabytes of data every day. This data includes pictures, videos, messages, and more.

In contrast, emails fall under semi-structured, and your pictures and videos fall under unstructured data. All this data combined makes up Big Data. 

What is Big Data Analytics?

I will explain this definition by way easily. Big Data analytics is a process used to extract meaningful insights, such as hidden patterns, unknown correlations, market trends, and customer preferences. Big Data analytics provides various advantages—it can be used for better decision making, preventing fraudulent activities, among other things.

Why Big Data Analytics?

The company has nearly 96 million users that generate a tremendous amount of data every day. Through this information, the cloud-based platform automatically generates suggested songs—through a smart recommendation engine—based on likes, shares, search history, and more.

If you are a Spotify user, then you must have come across the top recommendation section, which is based on your likes, past history, and other things. Utilizing a recommendation engine that leverages data filtering tools that collect data and then filter it using algorithms works. This is what Spotify does.

And, especially advantages of Big Data analytics

1. Product Development and Innovations

Use Case: Rolls-Royce, one of the largest manufacturers of jet engines for airlines and armed forces across the globe, uses Big Data analytics to analyze how efficient the engine designs are and if there is any need for improvements.

2. Risk Management

The organization leverages it to narrow down a list of suspects or root causes of problems. Big Data analytics to identify fraudulent activities and discrepancies.

3. Improve Customer Experience

The airline identifies negative tweets and does what’s necessary to remedy the situation. By publicly addressing these issues and offering solutions, it helps the airline build good customer relations.

4. Quicker and Better Decision Making Within Organizations

They will analyze several different factors, such as population, demographics, accessibility of the location, and more. Starbucks uses Big Data analytics to make strategic decisions. For example, the company leverages it to decide if a particular location would be suitable for a new outlet or not.

SHARE THIS