NOTE: If you are finding this lab via the Microsoft Virtual Academy recording: WELCOME!!! We want to let you know that the workshop continues to evolve and you will likely find some differences between what you see in the recording and what you will find in this up-to-date and living manual. For example, after the recording, the first exercise (building an Azure ML model) was changed quite a bit to move more of the steps to R script. The essence of the workshop, however, is still intact and you should be able to follow along.
AdventureWorks Travel (AWT) provides concierge services for business travelers. In an increasingly crowded market, they are always looking for ways to differentiate themselves and provide added value to their corporate customers.
They are looking to pilot a web-app that their internal customer service agents can use to provide additional information useful to the traveler during the flight booking process. They want to enable their agents to enter in the flight information and produce a prediction as to if the departing flight will encounter a 15 minute or longer delay, taking into account the weather forecasted for the departure hour.
In this workshop, attendees will build an end-to-end solution to predict flight delays taking into account the weather forecast.
The workshop uses several, but not nearly all, of the components that are part of Cortana Intelligence Suite. The goal is to show an end-to-end solution and not necessarily try to work in every component possible. The workshop architecture is below and includes: