“Big Data makes us smarter, not wiser.” – Tim Leberecht.
The term ‘Big Data’ got introduced in 1940s. Companies around the world have put in ceaseless efforts to explore its potential. The global tech giants have massively increased their spending on leveraging big data technologies. This trend got quickly replicated among major industry players.
As a result, according to a forecast issues by research firm(IDC), big data technology and services will grow at a CAGR of 23 percent through 2019. The big data annual spending will reach $48.6 billion in 2019.
That’s how big data services are being accepted worldwide!
Big Data has given a ‘ray of hope’ to companies and enabled them to make use of data of any size and volume. The bits of data collected via our mobile phones, GPS, sensors devices is no longer useless. Every bit of data collected gets collected and processed to derive useful insights about us (customers).
Amidst, the increasing benefits of Big Data, people fail to see the things it “can’t” do. This was surprising for me too. But soon I realized, Big data always complements business intuition but can’t ever replace it.
In this article, I present you my research of last 7 days. My crazy curiosity led me here. I just couldn’t digest the fact that big data has all it takes for a company to succeed. Big Data is ‘capable’ of many things. But ‘incapable’ too.
Note: My thoughts are not exhaustive but an attempt to put a framework. Feel free to add your perspectives in the comments section below.
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This exercise will prepare us for the future. We must know about things which are yet to come. Hence, If you are reading this, I invite you to take a stab on this question. You just need to write(I’ve already shared the answer though):
” 5 things which Big Data can do” & “5 things big data can never do”.
For instance, if I conclude using a logic that X is not possible using any technology platform with Big Data. I will simply eliminate all the business problems which are related to X. Getting it?
Below is my list. If you disagree with any of the element in my list, please justify! I will love to modify this list with time. Let’s start with a short note on my ideology on using business intuition and business analytics
The rule says,
“80% of time is spent in creating stories from past data, and 20% of time is spent in connecting those stories with current business”
Explanation: I believe no analytical insights are useful until they are in sync with business intuition. Agree ? Moreover, with time, the data driven component has grown exponentially. Companies are now flooding with data. But would that really make a difference? No!
Companies must realize, a right combination of successful business analytics over required business intuition is in ratio of 80:20.
If we can build a story using analytics which describes the past to predict future expectations 80% of time, we need to invest 20% of time thinking, how this information is useful to business. We must think of ways which can change our future and meet our broader business objectives. This requires a strong business understanding and sound knowledge of business rules.
The 20% component in this rule is non-replaceable. Hence, humans intervention is required for solving this 20% and possibly no machine can make up for it. Not even artificial intelligence. Because, humans think in a non-defined fashion which leads to creativity. Creativity is what I believe no machine can bring to the table. My list is inspired though this rule.
I believe this article will reach its true potential if people start trying out the exercise in this article. Try thinking in a more holistic view where you can see what machine cannot do ever. For instance, my starting point was the 80:20 rule that machine cannot bring creativity. This starting point helped me think of what are the pieces which needs creativity in the process of analytics.
What is your list of do/don’t? Did you like this post? Write your comments in the box below.
Thanks Tavish, Great article. I loved it and actually I am thinking of sharing it with my circle of network. Of course source will be acknowledged in some form. Any objection? Regards,
Sure. Go ahead. Request you to add your list as well.
Good article Tavish.
Thanks Tavish for posting good article. most of the companies are thinking in such away that they would like to change their database schema models in terms of Big data without knowing what it is. so your article may helpful to those companies. as big data analysis is always a data driven approach to improve the growth of organizations to make future decisions. Big data is not a computational approach. big data analysis is like a "trying to search for black cat in dark room which there in it" .like insights of data to find
Hi Tavish, Good article to have high level categorisation of What Big Data can do and what it can't accomplish 100%. I have one more question on Big Data capability in Data Security or Overall Security. Whether it should be handled by Technology alone or should be govern by strict cyber law?? The reason why I am asking is. It's one of the challenges of adopting Big Data in Banking.
a very simple and easy to understand one. Thanks for your article Tavish. But, I have a small question - as per your article Big Data resembles to Machine. Of course it is...specially when AI is to make machine intelligent. But the purpose of Big data is not the only one, I think. However, I will expect you to put more insights into it in near future. - from an aspiring business analyst.