Column monitors

What is a Column Monitor?

A column monitor in Soda tracks a specific statistical metric for a given column over time. It helps detect unusual patterns or unexpected changes in column behavior, such as spikes in missing values or shifts in averages.

You can find column monitors by opening the Metric Monitors tab on any dataset and scrolling to the bottom of the page. This section lists all active column monitors in a structured, searchable view. The list can be sorted by recency or by the number of detected anomalies, allowing you to quickly focus on the most relevant issues.

Unlike dataset-level monitors, which can be applied at the data source level, column monitors are configured at the dataset level and are tailored to specific use cases. It is recommended to add column monitors only to columns where changes are likely to reflect actual data quality issues. Adding too many monitors may increase false positives and create unnecessary noise.

For column monitors to work, a time partition column must be defined. Soda uses this column to divide the data into time-based partitions, typically by day, and calculates the selected metrics within each partition. The column must be a timestamp and should reflect when records arrive in the database to ensure accurate and meaningful results.

For each dataset, you’ll see a scrollable list that includes:

  • Result of the anomaly detection: Anomaly, Expected or Unkown (not evaluated yet)

  • Column name

  • Metric name (e.g. Missing values percentage, Average)

  • Column being tracked

  • Latest value

  • Trend sparkline

At the bottom of the list it is possible to load more monitors. And every monitor can be deleted and configured with opt-in notifications.

Types of column monitors

Data type
Metric
Description

All data types

Count

Detects anomalies in the number of non-missing (non-NULL) values in a column.

Duplicate percentage

Detects anomalies in the percentage of duplicate values in a column.

Maximum value

Detects anomalies in the maximum (highest) value in a column.

Minimum value

Detects anomalies in the minimum (lowest) value in a column.

Missing values percentage

Detects anomalies in the maximum (highest) value in a column.

Unique count

Detects anomalies in the number of distinct (unique) values in a column.

Timestamp

Most recent timestamp

Detects anomalies in the most recent (latest) timestamp value in a column.

Numeric

Average

Detects anomalies in the average (mean) value of a column.

Standard deviation

Detects anomalies in the standard deviation of values in a column.

Sum

Detects anomalies in the total (sum) of values in a column.

Variance

Detects anomalies in the variance (spread) of values in a column.

Q1

Detects anomalies in the 25th percentile (first quartile) value of a column.

Median

Detects anomalies in the 50th percentile (median - Q2) value of a column.

Q3

Detects anomalies in the 75th percentile (third quartile) value of a column.

Text

Average length

Detects anomalies in the average character length of text values.

Maximum length

Detects anomalies in the shortest character length of text values.

Minimum length

Detects anomalies in the longest character length of text values.

More metrics and monitors will be released in the future.

Add Column Monitors

Column monitors can be added one by one or in bulk. When multiple columns are selected only metrics that are applicable to all columns will be shown.

  1. Open the column monitor wizard

  • In the Metric Monitors dashboard, click Add Column Monitors.

  1. Select columns

  • Search or scroll your table’s columns.

  • Check one or many boxes to select columns in bulk.

  1. Pick metrics

For all column metrics:

  • Select the metrics of interest.

  • Search or expand metrics for further configuration:

    • Valid Range: define MIN and MAX values the metric can take (defaults to –∞/∞ or 0–∞ for time-based metrics).

    • Threshold Strategy: choose whether to alert on the Upper range, the Lower range, or both.

    • Exclusion Values: specify literal values or ranges to ignore when marking anomalies.

  1. Add monitors

  • Once you’ve selected your columns and toggled the desired metrics on, click Add Monitors.

  • Empty monitors will be added to the list

  • And at the top of the page you will be prompt to run a Historical Metric Collection Scan.

Configure and fine-tune Column Monitors

Column Monitors can be configured when setting them up and while they're in production. To fine-tune the monitor to your specific needs, go to the page for each specific metric.

Learn more about How to fine-tune Metric Monitoring →

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