Exercise and use case overview
The sample data in this exercise is representative of data sources that would be used in transportation or fleet usage data analytics. The queries in this chapter can be replicated and reused with actual business data. As transportation data is rich in location and geography information, we will use the BigQuery GIS and geospatial analytics (https://cloud.google.com/bigquery/docs/geospatial-intro) approaches described in the Google Cloud docs [2]. See the following diagram for our example data source and some of the columns that will be used to derive insights.
Figure 12.2 – Transportation data and visualization tool approaches
Reviewing Figure 12.2, you can see the gps-data table and the columns that we will use in this hands-on example. We will do some basic data preparation in this example to get to the insights quicker and will change the TIME column to DATE data type so it can be more easily displayed in charts...
