You’re missing out on somethingMakarand Vaidya
It was a very busy evening at the beach. After the day’s work, I was relaxed and decided to spend some time watching the buzz around. A few kids were busy building a sand castle. They were so engrossed and bothered little about what was going around. A few other kids were playing football on the sands, focusing on the ball that was being tossed around. A few young adults were stepping in and out of the water. Some were busy watching the sunset, some were trying to locate a perfect spot for a selfie with the setting sun. A few vendors were trying to sell some stuff moving around looking for customers. A stray dog had planned to have dinner on the beach and was searching for leftover food in the dust bins.
Everyone had access to everything around. There were literally thousands of things that could be observed. It was humanly impossible for anyone to observe everything. Everyone was clearly focused on the object of their interest. Did they miss out on other things they could not watch? They sure did.
We encounter a similar situation while planning for a machine learning exercise. In any large enterprise, there is a huge amount of data distributed across various systems, and it is just impossible to look at everything at the same time. Things become a bit easy when you know exactly what you want to look for. A clear focus also reduces the amount of data that needs to be stored and handled.
Does it mean we will miss out on something? We sure will.
On the beach, there were many people looking at different things in the same environment. Similarly, we can have different parallel observers looking for different things in the data. The machine’s ability to look at multiple things in parallel definitely helps in this situation.
Have you already identified a few things to look for?