Option 3: Replace Missing Values with an Estimated Value - Advanced SQL Engine - Teradata Database

You can estimate a value to update the rows with a missing value.

The example shows this for the TEMPERATURE column in Table and Data Definition for Time Series Aggregates Examples. The example updates all missing values in each timebucket with the average of the present values:

Create table ocean_buoys2 as ocean_buoys with no data;
INSERT INTO OCEAN_BUOYS2 VALUES(TIMESTAMP '2014-01-06 08:00:00.000000', 0, 55, );
INSERT INTO OCEAN_BUOYS2 VALUES(TIMESTAMP '2014-01-06 08:09:59.999999', 0, 55, );
INSERT INTO OCEAN_BUOYS2 VALUES(TIMESTAMP '2014-01-06 09:01:25.122200', 1, 55, );
INSERT INTO OCEAN_BUOYS2 VALUES(TIMESTAMP '2014-01-06 09:02:25.122200', 1, 55, );
 
MERGE INTO OCEAN_BUOYS2
USING (SELECT TD_TIMECODE, BUOYID, Avg(TEMPERATURE) FROM OCEAN_BUOYS GROUP BY (TD_TIMECODE, BUOYID) WHERE TEMPERATURE IS NOT NULL) AS S(a,b,c)
ON TD_TIMECODE=S.a AND BUOYID=S.b AND TEMPERATURE IS NULL
WHEN MATCHED THEN UPDATE SET TEMPERATURE=S.c;

select * from ocean_buoys2 order by 1;

Result:

SELECT $TD_TIMECODE_RANGE, $TD_GROUP_BY_TIME, BUOYID, AVG(TEMPERATURE), COUNT(*)
FROM OCEAN_BUOYS
WHERE TD_TIMECODE BETWEEN TIMESTAMP '2014-01-06 08:00:00' AND TIMESTAMP '2014-01-06 10:30:00'
AND BUOYID=0
GROUP BY TIME (MINUTES(10) AND BUOYID)
ORDER BY 2,3;

Result: Note the effect on the Average column.