Big Data Analytics
What is Big Data Analytics?
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 is big data analytics important?
In today’s world, Big Data analytics is fueling everything we do online—in every industry.
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. What enables this is the techniques, tools, and frameworks that are a result of Big Data analytics.
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.
But, let’s get back to the basics first.
What is Big Data?
Big Data is a massive amount of data sets that cannot be stored, processed, or analyzed using traditional tools.?
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.?
Data also exists in different formats, like structured data, semi-structured data, and unstructured data. For example, in a regular Excel sheet, data is classified as structured data—with a definite format. In contrast, emails fall under semi-structured, and your pictures and videos fall under unstructured data. All this data combined makes up Big Data.
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Uses and Examples of Big Data Analytics
There are many different ways that Big Data analytics can be used in order to improve businesses and organizations. Here are some examples:
These are just a few examples — the possibilities are really endless when it comes to Big Data analytics. It all depends on how you want to use it in order to improve your business.
History of Big Data Analytics
The history of Big Data analytics can be traced back to the early days of computing, when organizations first began using computers to store and analyze large amounts of data. However, it was not until the late 1990s and early 2000s that Big Data analytics really began to take off, as organizations increasingly turned to computers to help them make sense of the rapidly growing volumes of data being generated by their businesses.
Today, Big Data analytics has become an essential tool for organizations of all sizes across a wide range of industries. By harnessing the power of Big Data, organizations are able to gain insights into their customers, their businesses, and the world around them that were simply not possible before.
As the field of Big Data analytics continues to evolve, we can expect to see even more amazing and transformative applications of this technology in the years to come.
Benefits and Advantages of Big Data Analytics
1. Risk Management?
2. Product Development and Innovations
3. Quicker and Better Decision Making Within Organizations
4. Improve Customer Experience