Data Smart: Using Data Science to Transform Information into Insight

Data science is the transformation of data using mathematics and statistics into valuable insights, decisions, and products.

This chapter looks at a set of forecasting techniques called exponential smoothing methods.

best model is one that strikes the right balance between functionality and maintainability. If an analytics model is never used, it's worthless.

Just when you think you have a good demand forecast, a flood disrupts your supply chain, limiting your supply, forcing you to raise prices, and throwing your sales completely out of whack.

Your goals should be things like using data to facilitate better targeting, forecasting, pricing, decision-making, reporting, compliance, and so on. In other

You get more bang for your buck spending your time on selecting good data and features than models.

Identify the analytics opportunities you want to tackle in as much detail as possible before acquiring tools.

“Why didn't you use support vector machines or neural nets or random forests or boosted trees?” There are numerous types of AI models all with their strengths and weaknesses. And I would encourage you to read about them, and if in your

It's spent moving data to send through the AI model. It's not spent running the AI model, and it's certainly not spent training the AI model.