Data science: A Blend of These Data Components

Data science: What is it?

Those who are a little new to the field should first know what data science is at all. So, most of you should not have much problem in agreeing that the current era is the era of data. Data is collected, stored and processed by individuals, groups, and large business firms throughout the world. Data science is the very field that deals with all the problems involving data. It is a very vast and highly multi-disciplined domain and its applications and reaches are rooted far more extensively than you can even imagine of.

As I’ve already mentioned, data science is a multi-disciplinary sphere and is contributed by many data related fields. These fields are described precisely in the following part of this article.

Different Components of Data Science

1)      Big data- The term “Big Data” is used to address the unusually large and extraordinarily complicated sets of data that can’t be even though of to be solved using the old traditional data management techniques. We know that data is being created each and every second from many sources, including company databases, cameras, microphones, IoT networks, and many other sources. The amount of data being stored per day now accounts up to several zettabytes.

2)      Data mining- Data mining is the process of processing raw data with the intention of extracting more understandable trends or patterns out of it. This makes the data easier to work on at the subsequent steps. It is used for predictive analysis i.e. finding out the possible behavior of the data on the basis of the patterns in the pre-existing data.

3)      Data analytics- Data analytics can be understood as the set of qualitative and quantitative techniques and processes involved in solving business and commercial problems and aiding in taking decisions which result in maximum benefit or gain.

4)      Data analysis- Though it may sound similar to the previously discussed component- “data analytics”, data analysis is a little different from it. In fact, data analysis is a part of data analytics. Data analysis is the set of processes involved in examining data for taking decisions to fulfill business objectives.

5)      Machine learning- Machine learning is the study of computer algorithms and statistical models which is used to train machines to perform some specific operation by giving them sample tasks and teaching them how to respond. Machine learning is a very vast field in its own. One of the biggest and most promising applications of machine learning is in artificial intelligence. It teaches machines to do such tasks which were earlier regarded to be the privilege of humans only.

So, these were the main components which frame together to make the huge arena of data science. Whether it resonates with you or not, data science has innumerable applications in the commercial world as well as your personal life.

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