Data Science – The three pillars

What is Data Science?

Data Science is more than just a word.With the universe constantly being explored, there is constant production of data too. Data that helps universe evolve and grow further. But this data needs to be decoded first to be of any use. And this is what can be designated as Data Science.

But decoding Data Science is not that simple. It comprises primarily of 3 constituents and each one of them needs to be done with precision for the data to actually make sense.

  1. Data Structuring

Data Structuring is the simple procedure of compiling data into a coherent format. For the data to be anatomized, there is a plethoric need for the data to be organized. Data structuring does not simply mean sorting data. It also means providing data with an edifice. Data may be of many different types, from different sources. There might occur a scenario where the raw facts available may not be in the same layout. Configuring this data would need manual or machine support. Previously data could be managed manually.

But since the advent of Big Data, it is no more a possibility. Dependency on various software has increased by a huge margin to make this task easy hassle-free. But this is a very basic step towards effective business intelligence and so it can’t be neglected or done haphazardly without the right approach.

  1. Data Analytics

When the available facts and figures are given a proper and workable conformation, is the time to analyze it. Data Assessment is done on the basis of certain parameters that are extremely important and often industry specific. This leads to the procedure of deconstruction and then regrouping of data wherein, the information needed is given a clear visualization space.

This is consequential step in the process wherein actual useful insights are extracted. It is often difficult to define this step in terms of timeline but often the amount of time taken is in proportion to the data size. However, technology has made it possible for the whole process to become lightning fast wherein tonnes of data needs a blink of an eye to complete.

  1. Data Visualization

Data is given a formation and substantial information is extracted. But how will this data be available to the user? If we would have been in a situation 10 years ago, the apparent answer would have been manually extracting and presenting in excel. But technology has progressed and emerged as the answer to all exacting challenge. Data Visualization Software help in presenting data in visually appealing and impressive manner. Viewing data in pictorial format increases the inherent understanding and also can be done in real time. And this is the last and most important step of Data Science.

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