Data has grown more in the last decade then all past years combined. Data growth particularly took a flight when web 2.0 was introduced. It allowed users to create data of their own. Big corporates with millions of users had to store data generated by all of them. They could delete all that data, but it would have been a waste. You see data is really the biggest asset of a firm. These corporates allowed user and platforms to generate data so they can get to know them better. This way they are left with millions of petabytes of raw data. Now the difficult part was to extract useful information out of this massive crowd. This is exactly why disciplines like Data Mining, Big Data, and Data Science was introduced. Today there are thousands of students all around the world learning Data Science that is considered to be an important player in the future of information technology.
Why Do They Need Data?
Web 2.0 doesn’t just allow users to generate data. The platforms also keep creating data about the users. For example, Facebook records when you came online, how long did you stay, and what did you do in that time; and it’s done every day. The question is, why they are storing so much data. A simple answer would be to learn more about their users. They want to learn as much as they can so they can make better use of you to earn more. Of course, they are not going to make you do labor. They can use this information about users in many different ways.
For example, show you ads that you will find interesting and at a time when you are likely to be interested in them. Moreover, the same data is used to learn more about the platform and to provide a better user experience. It is by providing the best experience that these corporates can beat their competition. Name any big IT company today; you will see that they are collecting data and using big data.
How is This Data Utilized?
Big Data is a discipline that analyses massive amounts of data using computational methods to reveal and understand its patterns to extract useful information. There are several tools like RapidMiner, Apache Storm, and R Programming used to help efficiently execute big data techniques. Many software houses also provide the service of big data and data mining to their clients. Not only that, well-reputed IT firms like GK Group HC also incorporate big data into their backend development services. This allows them to create artificially intelligent programs.
Artificial Intelligence is dependent on the program to learn itself. Big data uses computational methods to extract useful information, and computers only understand calculations. There are machine learning engineers that, with the help of data scientists, create codes that collect a large amount of data, analyze and filter it, and extract insights to provide a better service and user experience.