Problem formulation/ideation (business understanding)

In this stage, as a data scientist, you primarily work with different stakeholders to understand the business problem you are trying to solve. You work with business leaders to define the problem and the expected outcome of the project and then work with the data engineering team to get access to data for building and training ML models to solve the defined business problem.

To learn how to conduct an end-to-end data science implementation with Fabric, we will be using the NYC Taxi & Limousine Commission – yellow taxi trip records dataset (https://learn.microsoft.com/en-us/azure/open-datasets/dataset-taxi-yellow) from Azure Open datasets. The records in this dataset contain fields such as pickup and drop-off dates/times, pickup and drop-off locations, trip distances, payment types, itemized fares (fair amount, tax amount, and tip amount), rate types, and driver-reported passenger counts. This dataset contains 1.5 billion...