The emergence of Data Science – Need for Data Science


Okay, on readers demand we have created a dynamic series called “Emergence of Data Science”. Today we live in the world of data where storing and managing big data is the main concern. Whereas storage part of data has been already taken care of the help of frameworks like Hadoop. Now, the part of managing data is referred to as Data Science.

In this series, we are going to cover numerous aspects of this data management process. Precisely we are going to cover the following parts in this series;

  1. Need for Data Science.
  2. What is Data Science?
  3. How it’s different from Business Intelligence and Data Analysis?
  4. The utilization of Data Science with an active example.

If you follow this series carefully, then by the end you will know what is all this fuss about data science and how can you use it to drive insight information from a large amount of data.

Why Data Science is Vital?

#1. Data Structure has Changed

Traditionally, data is well structured and sorted into small parts. It is easy to manage structured data to get insight information for business intelligence. But, today the nature of data has totally changed. Nowadays, data is becoming more and more unstructured which is difficult to manage and interpret. According to a report, by 2020, 80% of data will be unstructured.

This unstructured data will be gathered from different sources like financial logs, text files, multimedia forms, sensors, and instrument. It is impossible for simple BI tools to process this large amount of data and analysis it. For this advanced and complexed processing, analyzing and managing tools are required. This is the biggest concern of industries today and that’s why they are exploring different segments of data science to manage a large amount of unstructured data.

#2. Better customer service

Do you want to intercept the requirements of your potential customers from their past browsing history, purchase history, age or income? Indeed, this feature has already present and numerous business owners have taken advantage from it. But, when the area of data gets increased with the help of perfect management of it, then you can use data more effectively to generate user-friendly products. You can enhance the growth of your business with proper data management.

#3. Advanced decision making

Are you waiting for automatic cars? Then, your this dream will come true with the data science also. The self-driving cars collect live data from sensors, including radars, cameras, and lasers to create a map of its surroundings. On the basis of this collected data, automatic car’s make the decision like when to turn, when to stop, when to overtake and where to go. So, this management of data helps in making correct decisions also.

#4. Predictive Analytics

Data can be used to draw predictive analytics models such as weather forecast. The data collected from the ships, satellites, aircraft’s, radars, etc., is used to build the models. These forecasts won’t only help in determining the weather, but also helps in predicting the natural calamities. This way today we can save numerous lives with the help of correct data prediction.

Well, requirement list of the data science can go even longer, but with these four points, you might have to get some basic idea. The idea that data science is the core of all the latest and upcoming technologies, so if you want to invent a new technology, then you need to understand everything about the scientific way of managing data. We will share detail insight on the topic in the next article, so stay tuned.

About the author

Arpit Agarwal

I am a freelancer content writer, web developer and Video editor who loves to write technical stuff and on the other hand makes awesome videos as well. I like to make people happy with my writing and also try to make sure, you come back to read more.

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By Arpit Agarwal

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