What "Big Data Analytics" Implies In Different Industries - HPC ASIA
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What “Big Data Analytics” Implies In Different Industries

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Hamideh Iraj

Hamideh Iraj

I have been studying about the applications of big data analytics in different industries for the past few months. What I realized is that the term “big data analytics” has some implicit meanings across different industries. Each of the three words “big”, “data” and “analytics” has its own maturity and age! Sometimes two of these three are twins and sometimes all three are triplets.

On the picture, you can see the characters for big, data and analytics from left to right accordingly. Pictures were created using GoAnimate.

Here are the stories:

  • In Manufacturing industry data existed from long ago and it was big in terms of volume and variety from the birth of data and analytics was also common from the very beginning. Therefore, big, data and analytics are one of the oldest among industries and they almost have the same age. You can characterize them as three old men standing together. What happened during these years is that the number of data sources and the complexity is growing.
  • Retail industry is somehow similar to manufacturing industry in the meaning of big data analytics. Both industries are data-intensive, customer-oriented and they are both taking advantage of digital transformation. Again there are three old men standing together.
  • In Education industry, data was brought by E-Learning Systems so it is young (Perhaps in her twenties!). Interestingly, big data and analytics were born somehow together. When data was gathered in mass, people started to think that what kinds of questions it can answer. It is worthwhile to mention that big data in education is not big in volume but it is the newness of the idea that matters and matching data to represent concepts is challenging. Finally MOOCs scaled E-Learning Systems. Although they have different functions, MOOCs enabled researchers to study some new concepts in learning such as learning patterns, communication patterns and so on. Here we have a twenty-something lady with two daughters standing together. Big is a little girl, data is a lady and analytics again a little girl.
  • In Healthcare industry data existed from long ago in isolation. It is big in terms of volume and variety i.e. many different data sources and different formats (digital records, handwritten prescriptions, hospital records, scans…). Big and data are rather young (I mean digital data) and analytics is a little boy.
  • In Government data was brought by E-Government systems. It has been big in terms of variety. Analytics has started when E-Government program was successfully implemented. Therefore, big and data are young and analytics is a little boy.
  • In Social Sciences data analytics is not new. Data was gathered through surveys and lab experiments and was analyzed by social scientists. Gathering data was difficult, expensive and sometimes data was biased. Big data sources such as social networks and applications on mobile devices gave a new spirit to social sciences so Big Data brought its own analytics into action. Here big data analytics is different from old data analytics.
  • In Sports, Big data is new. Sensors make a ton of data to help athletes and coaches perform better. Data existed for long. But it was difficult and sometimes impossible to gather. Analytics is not new but different from old analytics based on manual booking of actions on the game.

It was my understanding of big data analytics. What do you think about big data analytics in your industry?

Author Bio:

Hamideh Iraj is a big data and data science researcher. She writes on a wide range of topics including Big Data, Data Science, Information Technology, Education and MOOCs.

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