In this tutorial, you will learn how the xyzt.ai platform can be used for analysis of historic taxi usage in New York (including average fare, passenger count, and trip distances). You will first learn the type of time series data the platform can handle, including the explanation of the example data set we will be using in this platform. You will then create a new project and attach an existing aggregate time series data set. You will then perform following analysis tasks:
Using the visual analytics capability
Analyze two regions with different fare and usage statistics.
Perform density analysis to identify regions with many query results.
Using the trend analytics capability
Analyze and compare the change in average taxi fare amount for different regions and different time of day.
Export the computed results to a CSV file for opening again in another tool, such as Microsoft Excel.
In addition, you will learn how to build a dashboard with your analysis results and how to share it with your co-workers, or your external audience such as policymakers or the press.
Free trial accounts do not support uploading your own data
For this tutorial, we will be using data that is already in the platform.
Get in touch if you want to start uploading your own data, and you are using a free account.
Watch the introduction movie instead when short on time
If you don’t have time right now to follow this tutorial, you might be interested in our introduction movie.
In 6 minutes, it will show you the most important features of the platform.
Go to the next part: Understanding aggregate time series data