Aggregate data by time

Description

The Aggregate Data by Time activity enables you to group and summarize records based on a time-based column, such as order date, timestamp, or transaction date. You can define the aggregation period (e.g., month, year, week, day) and apply aggregation functions like sum, average, and count on numerical columns.

Use this activity to:

• Group rows into periods such as months or weeks.
• Summarize numerical data by time ranges.
• Retain or exclude original columns from the output.
• Decide how text values are handled when grouped by time.

Use case: After importing a sales dataset, this activity can be used to generate monthly sales summaries, average unit sales per week, or total transactions per year.

Input

Input Type	Required	Description
Data	Required	Tabular input data with text or numeric columns to concatenate

Output

Output Type	Format	Description
Data	JSON	Aggregated dataset by time period

Configuration Fields

Field Name	Description
Time Column	The column containing time/date values used for grouping.
Period	Defines the time interval to group by. Options: year, month, week, day.
Aggregations	List of column-to-aggregation mappings. Column Name – Column to aggregate Aggregation Type – sum, average, count
Include Original	Toggle to retain the original input data columns. If disabled, only aggregated columns are returned.
Text Strategy	Specifies how text fields are handled in grouped data. Options: First – Use first value Last – Use last value

Sample Input

Order Date	Sales	Units Sold	Transactions	Product Name
2024-01-10	500	10	1	Product A
2024-01-15	700	12	1	Product B
2024-02-05	300	5	1	Product A
2024-02-25	900	15	1	Product C

Sample Configuration

Field	Value
Time Column	Order Date
Period	Month
Aggregations	Sales → sum Units Sold → average Transactions → count
Include Original	false
Text Strategy	First

Sample Output

Month	Total Sales	Avg Units Sold	Transaction Count	First Product
2024-01-01T00:00:00	1200	11	2	Product A
2024-02-01T00:00:00	1200	10	2	Product A