Aggregations

Aggregations turn reporting data into interactive charts. Each aggregation reads from a report, groups the data over a time range that you choose, and shows the result as a chart with one or more measures.

Two aggregations are currently in beta: Ridership and Served demand. Beta means the feature is available but not yet stable, so its behavior may still change. For how release stages work across Reporting, see Release strategies.

Beta

Ridership and Served demand are released to beta. They are visible and their data is accessible, and the interface indicates the beta stage.

  1. How an aggregation works
    1. Time granularities
  2. Ridership
    1. Measures
    2. Filters
  3. Served demand
    1. Dimension
    2. Measures
    3. Filters

How an aggregation works

An aggregation is built from a small set of building blocks:

  • Visualization. The chart type used to display the result, such as a bar chart or a stacked bar chart.
  • Measure. A number that the chart plots, such as a count or a sum.
  • Dimension. A category that splits a measure into separate series, so you can compare parts of the total.
  • Time granularity. The size of the time bucket that groups the data along the time axis.
  • Filter. A condition that narrows the data before it is grouped.

Time granularities

You choose how finely the data is grouped along the time axis. The following granularities are available:

  • Hourly
  • Daily
  • Weekly
  • Monthly
  • Quarterly
  • Yearly

Quarterly and yearly granularities are new. They let you group data into calendar quarters and calendar years in addition to the finer granularities.

You can also pick a preset time range, for example Last 7 days, Last 12 months, Month to date, Quarter to date, or Year to date. The default range is Last 7 days.

Ridership

Ridership shows how many rides happened over time, together with the number of passengers. It is displayed as a Bar chart.

Ridership was previously named Rides.

Measures

  • Rides. The number of rides.
  • Passengers. The total number of passengers across those rides.

Filters

  • Product ID. Limits the data to one product.
  • Operator ID. Limits the data to one operator.
  • Booking type. Limits the data to prebooked or ad hoc rides.
  • Matching configuration. Limits the data to one matching configuration.

Served demand

Served demand shows how much demand was requested and how it was resolved. It is displayed as a Stacked bar chart, with each bar split by booking result so you can see how requests ended.

Dimension

  • Booking result. Splits each measure by how the request ended. The possible values are Completed, Booked, Cancelled, Booking failed, No booking, No offer, and Aborted.

Measures

  • Requested rides. The number of requested rides.
  • Requested passengers. The total number of requested passengers.

Filters

  • Product ID. Limits the data to one product.
  • Operator ID. Limits the data to one operator.
  • Booking type. Limits the data to prebooked or ad hoc requests.
  • Booking result. Limits the data to one or more booking results.
  • Winning requests. Limits the data to winning or losing requests. By default only winning requests are shown.