Today companies collect lots of data about their customer. They analyze clicks, visits, purchases, location data, social media shares, personal information, and more to understand customer behavior. Decades ago, collecting data was not easy. The problem these days is processing data into accurate information and getting valuable insights from it. We call this approach the DKIW pyramid.

In university, there was a marketing story about marketing research.

A marketer visited Africa for research about the market opportunities for shoes. He wrote in his report that "Nobody is wearing shoes here. There is no demand. We can not sell any shoes to these people"
A rival company sent another marketer for research. The report was different. "Nobody is wearing shoes here. We can sell millions of shoes here"

I don't know which marketer was right, but it is obvious that they were interpreting data differently. We are all doing the same. Most of the time, we have ideas and then use data to prove them right. We choose data to power our claims and ignore negative data. As a result, having data becomes meaningless.

https://towardsdatascience.com/rootstrap-dikw-model-32cef9ae6dfb

I don't have a perfect solution for this problem, but I think working with experts can be a good starting point. Most of the time, connecting dots will be a manual process. An expert with wisdom or knowledge about data will get better results than others. The experts can use data to test their ideas and ask more questions than others. Asking meaningful questions is the key point for interpreting.

I know we live in a data world. Every click, every heartbeat, and every data related to you is collected with trackers and stored in databases in clouds. Companies believe machine learning will process this massive amount of data and understand "what the customer wants?" I have some doubts about this claim. I'm sure algorithms will improve and be better for recommendations, but they won't be able to understand the reasons for any human behavior. This understanding is not about having lots of data and optimizing algorithms. Knowledge and wisdom are different from intelligence.

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