Discussion on:

Experts answer five critical big data questions

Last year I attended a conference at Daresbury Laboratory in the UK which was about Big Data. All the speakers were praising the advantage of this Big Data. When it came to discussion time, I brought up the ticket fiasco during the 2012 London Games when the public were unable to get into the computer to buy their tickets. I said it all sounds great having all of this data stored in the one place, but if your hardware is faulty, then your data is useless.
I went on to explain the cause of the problem and why people couldnt purchase their tickets. Some people at the conference spent several days trying to log into the computer. It took me two minutes to log in and purchase my tickets. There was nothing wrong with the computer, I just had to bypass the Enter button (link) and click on another link that took me to another page, and then I clicked other links that took me to the page on which I could buy my ticket.
The Games Organizers were very concerned about ticket touting and left the sale of the tickets to the last few days. There was a big rush to buy the tickets for the Closing Ceremony, and maybe 5000 or 10,000 or more, rushed to buy a ticket at the same time. The Enter button (link) (formula) would be confused and not respond. There was nothing wrong with the computer. Big computer, Big Data and small button and all was lost.
I explained this to the Organizers after the Games and there were no problems with the Paralympic Games.
John Ian Wing (UK)

Hi Teena

Can you ask Ken to rephrase his last paragraph, -

Actionable insight can help you build a 360-degree view of contacts and companies which result in an effective buyer engagement hub connected across channels. For example, you can combine your own customer data with third-party data, with buyer sentiment from social media activity, web activity and transactional data to better anticipate potential buyer needs. You can then use this foresight to target new customers more effectively through customer modeling, drive higher cross-sell and up-sell with existing customers through knowledge of corporate linkages, and proactively engage with current customers to increase retention through better customer service.

Ken, you have lost me on this one. Is it humans that will make the final decision or will it be the computer that makes the final decision?

I like Boyles response to the first step when considering big data, because it reminds me something I read recently about Smart Data being the monetization of machine-captured data through predictive analytics. So, as youre preparing to collect data, decide what to collect with monetization in the back of your mind. Its like setting SMART goals. Be specific on what you should collect, and why. Big isnt always better.

Robert Withers
Experian