BIG BI: Business Intelligence in Digital Transformation
Digital transformation is a broad term that has various meanings by application, but in general, it means that more and more of what organizations, people, governments do is happening in computers, mobile devices and networks. As a result, the way things are done is changing, especially in the way things are connected. So in this new world of data flying everywhere, being generated and consumed, where does one stop for a second to take a look at what’s going on?
In the old days, maybe 5-10 years ago, the obvious answer was analytical tools, such as BI or Excel, pulling data from a data warehouse. But something happened.
I like to call it a new theory of instatology. Everything changes, from why your kids don’t call you, they text you and put pictures on Instagram. Self-driving cars, your GPS system with turn-by-turn instructions knowing exactly where you are, annoying devices in grocery stores that talk to you as you pass based on (hopefully) a profile of what you may be interested in. Or a refrigerator that sends a message to your wife, “Neil is eating ice cream again.” Contrast this with an analyst sitting at a desktop developing a query for a report or a dashboard using information that hasn’t been updated since last night.
Now in the latter case, that really isn’t quite so bad as there are still a multitude of applications that are served by what we call classic Business Intelligence. Classic Business Intelligence isn’t going away, though it is becoming more intelligent. But in the other cases, there are a series of devices and flows that are needed that cannot operate with that sort of latency. Streaming out data is not BI, but when those flows ARE captured by business logic and help to deliver not only data but advice or even decisions, that is BIG BI.
The Two Forms of Big BI
Actually Big BI comes in two forms. The first, as mentioned above, is when BI kinds of logic are embedded in real-time or even near real-time systems. But Big BI can also mean the more traditional peripatetic analysis of interactive examination against the new and massive sources of data that were not part of traditional BI. In a way, you can consider this second type of Big BI of a Red Queen exercise, a concept discussed in the previous blog. It uses existing methods and tools for analysts to do their work, but expands the universe of data available to them. Sort of like keeping up with the Red Queen. It uses data as an asset to be exploited, keeping up with the trends to use the kind of data we see today in “big data.” But it doesn’t, on its own transform anything.
This first form, however, can be as wild as you can imagine. It’s cliché to repeat how massive computing and networking capabilities are today, the question is, how can you exploit decades of learning in tools like OLAP and BI to facilitate the digital transformation? In every area of digitally transforming the organization, such as customer experience, products and services and operations, ‘analytics’ are a key part of every operation.
