The Data Science Lifecycle Explained

You generate nearly two megabytes of data every single second just by existing. This massive explosion

of information is exactly why apps like Netflix seem to read your mind. It is not magic,

it is the Data Science Lifecycle. It starts with a clear business goal, not just random

math. You have to hunt down the raw data and usually spend months cleaning

it because bad inputs equal a trash model. Once prepped, you build algorithms that actually learn

and predict the future. But watch out, if you skip the evaluation phase,

your model fails in the real world. Data is the new gold, but only if you

follow the map.