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Cognite Data Fusion (CDF) pre-calculates the most common aggregates for numerical data points in time series. These aggregates are available with short response times even when you are querying across large data sets. Instead of downloading and manually aggregating data in an OData client, you can query CDF for the aggregates. Specify the time range and the granularity (the unit of time to compute the aggregates for) and let CDF do the computational work.

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Get aggregates for a single time series using the OData services​

In the asset-centric and data modeling OData services, when listing time series, the service exposes a function to retrieve aggregates for a single time series from CDF. To use the function in Microsoft Power BI:
1

Navigate to time series table

In the Power Query Editor, navigate to a list of time series table using a Cognite Power BI connector.
2

Select the Aggregate function

Use filtering to find the time series you want aggregates from, and then in the Aggregate column, select Function.
Locate the CDF OData connector in Power BI
3

Configure time range and granularity

Specify the time range and granularity, and then select OK.
Locate the CDF OData connector in Power BI
4

Review and finalize aggregates

The Power Query Editor displays a table with the aggregates for the specified time range. Remove the columns you don’t need, then select Close and apply.

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Get aggregates for many time series​

To retrieve aggregates from many time series in the same time range, use the TimeseriesAggregate function, exposed by the asset-centric OData service. Instead of calling the function on a single time series, create a time series table with all the time series you want to retrieve aggregates from. In Microsoft Power BI:
1

Add Timeseries table andTimeseriesAggregate function as new query

Open a connection to the asset-centric OData service using a Cognite Power BI connector. Right-click the Timeseries table and the TimeseriesAggregate function and add them as new query.
Locate the CDF OData connector in Power BI
2

Filter time series

Use filtering on the Timeseries table to find the time series you want aggregates from.
3

Configure function parameters

In the Queries panel, select the TimeseriesAggregate function and set the granularity, start time, and end time. Then select Choose column.
4

Select time series column

In the Select Column window, select your Timeseries table and the Id column from the table to specify which time series to fetch aggregates from in CDF.
Locate the CDF OData connector in Power BI
5

Invoke the function

Select Invoke to start retrieving the aggregates.
6

Review and finalize aggregates

The Power Query Editor displays a new table named Invoked Function in the Query panel with the aggregates for the specified time range. Remove the columns you don’t need, then select Close and apply.
If the TimeseriesAggregate function takes a long time to finish or fails after a long time:
  • Make sure you have filtered the time series table to contain only the time series you need.
  • Consider if you are using the right granularity. The granularity significantly affects the query performance.
  • Request a realistic number of data points. Aggregating large numbers of time series with short granularity may return vast amounts of data points, and Power BI doesn’t handle many gigabytes of data in a single query.