- Target – What you want to predict.
- Entity – Who you are making predictions for.
- Filters (optional) – Constraints on which entities or data to include.

Target
The target is the outcome you want to predict, defined after thePREDICT
command.
For example, to predict total purchases per user over the next 30 days, the target is “sum of purchases over the next 30 days.”
Entity
The entity is the subject of your prediction—who the prediction is being made for. For example, if predicting total purchases per user, then the user is the entity.Aggregation Operators
When predicting an aggregation over time (e.g., total sales over 30 days), use an aggregation function with a column reference. Example: Predicting Total Purchase Value per CustomerPQL
SUM(TRANSACTIONS.PRICE, 0, 30)
→ Sums purchase values over the next 30 days.FOR EACH CUSTOMERS.CUSTOMER_ID
→ Predicts for each customer.
SUM()
aggregation operator allows you to predict the total number of sales each customer will make in the next 30 days.

2020-01-01 00:00:00
, Kumo will aggregate all rows with timestamps t where 2020-01-11 00:00:00 < t <= 2020-01-31 00:00:00
.
When using aggregation with targets, both start and end values should be non-negative integers, and end values should be greater than start values.
Common Aggregation Functions
SUM()
– Total value over time.COUNT()
– Number of occurrences over time.
Aggregation Window (Start & End)
- The start and end parameters define the prediction window in days.
- If the prediction date is
2020-01-01
:10, 30
will predict transactions values from2020-01-11 to 2020-01-31
.
PQL
Aggregation Units
The time unit defaults to days, but can also be:days
(default)months
hours
PQL
Filters (WHERE
)
Filters refine a Predictive Query by removing irrelevant entities or restricting aggregation conditions.
For example, to predict purchases for active customers only (i.e., those who made at least one transaction in the past 30 days):
PQL
- Inline filters inside aggregations
- Nested temporal filters
- Static date/time filters
- Multiple target conditions (
AND
/OR
)