The harsh truth about the analytics industry is that “simple doesn’t sell”.
It’s challenging to advocate for simplicity in data architecture because simple solutions often appear effortless, and who wants to invest in something that looks easy? While everyone claims they want a straightforward data architecture, their purchasing decisions often tell a different story.
This is the insight that vendors of complexity have long understood. Complex and intricate data architectures tend to overshadow basic and streamlined designs. Complexity suggests something unique or cutting-edge, and it’s this perception of uniqueness that justifies the higher costs.
As a vendor or consulting company, you’re failing your customer if you give in to the temptation of technological complexity over clarity.
By prioritizing complex solutions that seem impressive but are harder to maintain and scale, you’re not serving your client’s best interests.
True value lies in designing data architectures that are not just elegant, but also efficient and sustainable. In the long run, these simple yet robust solutions will drive more success and satisfaction than any convoluted system ever could.
I know this is a bit of a rant without a solution, but let me follow up on that.
In the meantime, if you see stuff like this screenshot: Run forest, run!
