Missing Value Imputation | Teradata Vantage - Missing Value Imputation - Analytics Database - Teradata Vantage

Time Series Tables and Operations

Deployment
VantageCloud
VantageCore
Edition
Enterprise
IntelliFlex
VMware
Product
Analytics Database
Teradata Vantage
Release Number
17.20
Published
June 2022
Language
English (United States)
Last Update
2023-10-30
dita:mapPath
tuc1628112453431.ditamap
dita:ditavalPath
qkf1628213546010.ditaval
dita:id
sfz1493079039055
lifecycle
latest
Product Category
Teradata Vantageā„¢

If there are missing values in the data several modes are supported for the imputation of missing values both during the intermediate computation of an aggregate and in the result set for all timebuckets. Notice in the table created in Table and Data Definition for Time Series Aggregates Examples there are some null values for the TEMPERATURE column and not all the timebuckets are represented.

With missing values, consider the following:
  • How the missing values within a timebucket affect the result for that group; for example, should the missing values be ignored, treated as 0, or handled another way.
  • If you want a result for each timebucket, you must specify the manner in which this result should be computed (for example, should the result be ignored, returned with a constant value, and so on).

There are different approaches for each issue presented which affect the overall result obtained. The following describes the supported modes of operation for all time series aggregates and how to specify the desired behavior in SQL.

Note that only the AVERAGE function is used as an example, but the modes described apply to all aggregates.