Big Data – Big Dilemmas

There is lots of talk of big data. In short big data is just another term for analyzing an increasing amount of information that is gathered year over year about our daily lives, browsing habbits, etc. Take the following example: Suppose you were searching on baby names on the internet. The next time you log onto your favorite retailer’s site, they can tell by your history that you researched baby names. This now puts you in line for a barrage of coupons for baby diapers, strollers, supplies, etc. While the system won’t be perfect, you may not have been searching for yourself, you can forward the coupons on to the person that really was searching for the baby names and bingo- job accomplished. The coupon got into the hands of the person that would need them.

The above is one example of the more complex world of business analytics. Now for the Big Dilemma – how many places are you going to have to search for your data? Cloud computing could make this far more complicated than before. Consider a company with accounting, marketing, sales, shipping, receiving, IT and HR all reporting to mahogany row. Each department has its own head and budget and set of priorities for what it feels will increase business.

Sales moves to a cloud based model for all customer contact and CRM information. Shipping and receiving need to get updates to customer information. That is now two locations for information. Marketing needs to analyze their ad campaigns to see what has been most effective for a certain product. This incorporates web, customer and shipping and receiving (now three locations). Accounting wants to evaluate the pricing strategy on the promotion against shipments and customer demographics. Marketing needs to run some voice of customer for new products against some financial models. The merge/purge opt-in data base needs to be updated against recent customer information. Mahogany row wants to know who is buying what products by demographic to make a decision on an upcoming product release.

IT has to assure security across all locations (even if they don’t know where things reside). This is a complex problem with cloud as IT may be the last department to know about software going live in a department

As you can see, the data starts to get big, but with predictability, trends and forecasts can get even bigger. We may see a new title or two floating around as the intricacies, locations and complexity of data increase. Data forensic specialist? Data pathologist? Mad Data Scientist? We have come a long way from data and IT being a necessary evil to necessary to stay and grow in business.