I started in a financial controlling department of a large retail store in Belgium. There I used Excel to automate all the processes for controlling and reporting. Then when the data sets became too large for Excel, getting into Access and learning about databases, how you write SQL code. Once you know the front-end sub-functions of Excel and the backend SQL that's behind it, you can basically learn any BI tool on the market.
If people are looking to start data their data journey, they usually wind up in their research on the websites of the technology vendors, and they are selling business intelligence projects as a software that will solve their problems. But in fact, business intelligence is always a change journey. So you have to approach it like this. If you do BI well, then you will use the intel the the insights from the dashboards to improve your company, to improve the processes, and then also to maybe adapt the systems to those new processes. And then you go into a business intelligence cycle. So I think it's very important to make sure that the people who want to start using data are aware that if it's done well, it's always a transformational change for the organization.
In the past, you basically at the end of a project would have done a handover to the engineering team of the client so they can solve their own problems. Now, in many cases, you're kind of handing over to the AI. I think you still need a knowledge base to document things like architecture and high-level approach. The power of Gen.ai is to give the data environment in the hands of non-technical people who can think logically and who can describe the prompts they need to get the code they can use.
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