One of the greatest pitfalls in business intelligence is skipping descriptive and diagnostic analysis. As professionals in the BI space, we know there is a natural analytical progression – descriptive to diagnostic to predictive to prescriptive. In the business world this progression is being dangerously accelerated.
We are seeing an alarming number of students graduate from college without the ability to perform descriptive and diagnostic analysis. They have never heard of dimensional modeling, nor do they see the need for it. They are taught to take transactional data and directly input it into their predictive models. Businesses then follow the resulting prescription. Those that succeed praise the art of data science. Those that fail are silent. This dichotomy presents the appearance of success.
In business, since the ability to handle Big Data has come about, more and more companies have begun making decisions based on patterns from an extreme quantity of data. They don’t need to understand why the data is doing what it does – they just know that it does a certain thing – and if they make decisions based on that knowledge, they will be profitable. This is not sustainable.
We see this greatly prevalent in the world of AI. We at ConradBI have asked ChatGPT to write blogs and articles about business intelligence for fun. Please know we have never used them – our content is all our own. Of course, we were blown away by its abilities like everyone else. However, we never received any new insight. AI can only tell you what it has been told. And its tendency to repeat to you the loudest thing it has heard filters out the unique independent thought that sometimes is invaluable.
The Big Data and AI bubble will eventually pop. All tech bubbles pop. The companies that both understand their data with descriptive and diagnostic analysis while leveraging AI will be the ones that succeed at the next level. Here at ConradBI, we can lead you down a structured path using the latest technologies while futureproofing you for what’s to come.
