analytics is not technology

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Analytics is not technology, it is all about business Excerpt from article published at Economic Times CIO by Tapan, Executive Director, Sunstone Business School | 21 Jul 2014 If I made a Rupee every time someone said big data I would be a multi-crorepati by now. Over the past 3-4 years the word big data has been misused to represent anything and everything that remotely resembles data. The technology industry has done very little to clear the confusion but has rather added to it with numerous products and solutions claiming to do something or the other with big data have sprung up from big corporations to multitude of start-up tech firms. To add fuel to the fire and further their own goals sales/marketing teams of these technology firms have created a high level of confusion in the CIOs team in corporates. With half knowledge and the fear of being left out of something new (and great!) several investments are being made by corporates into analytics technology that will probably never see the light of day as far as business application is concerned. Feels like the dot com boom (surely it has not bust.. the balloon needs more gas) of the late 90s all over again Lets cut out all the jargon associated with analytics and big data and try a very simple definition (we should be able to explain this to our grandmothers in our mother tongue) and see what this animal really is. I will give it a shot and each of you can try your own versions: Every time someone makes a decision, they mostly rely on their past experience to increase the chances of getting the decision right. Analytics is a science that uses data to provide additional inputs to the decision maker so he/she can make a better decision combining his/her experience with the insights derived from data. Sounds rather banal compared to what your vendors have been telling you isnt it? Well it really is that simple. What complicates issue is the data that is resident with enterprises today and how to get the best insight out of that massive storage you have in your data center. The first step is really to get the business question right. Ask the right question and it will always be possible to figure out the answer by shifting through the myriad of data that you have available. In the beginning it may not be very efficient but then thats the precise role of technology to make this process more efficient. However, the key is still in getting the question right. Here are a few business questions from different functions that will get you started

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Page 1: Analytics is not technology

Analytics is not technology, it is all about business

Excerpt from article published at Economic Times CIO by Tapan, Executive Director,

Sunstone Business School | 21 Jul 2014

If I made a Rupee every time someone said big data I would be a multi-crorepati by

now. Over the past 3-4 years the word big data has been misused to represent anything

and everything that remotely resembles data. The technology industry has done very

little to clear the confusion but has rather added to it with numerous products and

solutions claiming to do something or the other with big data have sprung up from big

corporations to multitude of start-up tech firms. To add fuel to the fire and further their

own goals sales/marketing teams of these technology firms have created a high level of

confusion in the CIOs team in corporates. With half knowledge and the fear of being left

out of something new (and great!) several investments are being made by corporates

into analytics technology that will probably never see the light of day as far as business

application is concerned. Feels like the dot com boom (surely it has not bust.. the

balloon needs more gas) of the late 90s all over again

Lets cut out all the jargon associated with analytics and big data and try a very simple

definition (we should be able to explain this to our grandmothers in our mother tongue)

and see what this animal really is. I will give it a shot and each of you can try your own

versions:

Every time someone makes a decision, they mostly rely on their past experience to

increase the chances of getting the decision right. Analytics is a science that uses data to

provide additional inputs to the decision maker so he/she can make a better decision

combining his/her experience with the insights derived from data. Sounds rather banal

compared to what your vendors have been telling you isnt it? Well it really is that simple.

What complicates issue is the data that is resident with enterprises today and how to get

the best insight out of that massive storage you have in your data center.

The first step is really to get the business question right. Ask the right question and it

will always be possible to figure out the answer by shifting through the myriad of data

that you have available. In the beginning it may not be very efficient but then thats the

precise role of technology to make this process more efficient. However, the key is still in

getting the question right. Here are a few business questions from different functions

that will get you started

Page 2: Analytics is not technology

VP Marketing- Compared to all my media spend, how should I allocate budgets for the

digital media?

VP of B2B Sales- By what % is my sales likely to grow if I can increase the size of my

sales team by 10%?

VP Finance of e-tailer- Why are we spending so much on print media if a majority of

our customers reach our site through Google search?

As the technology leader in your corporation your role would be to:

1. Encourage business to ask more business relevant questions that will help the overall

business, without being worried about if your organization has the latest greatest

analytics technology. Beware, the sales teams of the same technology firms that are

calling on you in the morning are also calling he business leaders in the afternoon

and confusing them as much as they are confusing you.

2. Clear up the confusion on technology and bring back everyone to focus on business.

3. Get your tech teams to be more business savvy so that they can collaborate with

business teams better. They should have a substantial role in coming up with the

right analyses to spend time on rather than take orders from business and just

execute to those orders.

Lets not ignore technology completely. All your investments should be to organize data

in a manner that makes it easily accessible when needed more than anything else.

Depending on the volumes in your business you may need nothing more than that

traditional RDBMS in order to be able to satisfy business users with all the questions that

they can ever come up with. Stay away from exotic high promise new technology that is

springing up in every nook and corner in your city and mine.