Big Data (or how to make Business Intelligence keep up with the new times)

Large and small companies have always used the information within their reach to better understand their business and try to get better results.

With the advent of computers and the ability to store data systematically, new possibilities opened up. Data was collected at first in order to improve transactional processes. With sales and purchase information suitably stored it was easy to automate billing and restocking processes, and to improve management of the supply chain… However, we soon discovered that this same data, when suitably cooked, could be a source of unbeatable value.

At the start 2 plus 2 made 4

Companies have made an extensive and pervasive use of carefully gathered information. Thus, we have been able to respond to increasingly sophisticated questions: how much is invoiced each month? How much does it cost to produce each item? What products or product families provide the biggest margins? What will be sold next quarter?

The above questions can in fact be answered using a little, very well structured data. Basically, sales and costs data (by time, area, product and customer), suitably cooked, has served to satiate the hunger for information felt by analysts, product managers and managers of the companies that today supply our fridges, closets and leisure spaces.

This basic, structured data will certainly continue to be part of every organization‘s kitchen in the coming years.

However, companies are capable of generating and capturing ever greater amounts of data. The social networks where we interact, the phones we carry around with us, the loyalty cards we use to get discounts, or the cars we take to be serviced when the warning light comes on, are all clear examples of processes that generate (and store) more information about us and our habits.

We know that it is useless to gather without “cooking” it. How will this new data be cooked? And what for?

The second question is easy to answer: the data will be processed for the same reason data has been processed in recent decades, i.e. to sell more, win market share, know the customer, etc.