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Query

Columns visualizations are powered by a query engine. Most queries include:

  • Metrics: Values or aggregated values from your dataset
  • Dimensions: Keys used to break down metrics
  • Filters: Conditions used to narrow the dataset
tip

Different teams use different terms, so we use common industry wording. In this guide, Metrics/Values are numeric measures, and Dimensions/Keys are columns used for grouping or breakdown.

Metric (Value)​

A metric is a numeric field used to measure or aggregate data.

You can configure metrics to compute:

  • count of distinct values
  • row count
  • numeric aggregations such as sum, average, min, max, and percentile

Dimension (Key)​

A dimension is usually a text or categorical field used to group metrics. You can break down your metrics by any number of dimensions.

Pivoting is also available. It reorganizes data by turning one dimension into multiple columns while grouping by another. Pivot is available when:

  • only one metric is selected
  • multiple dimensions are selected

When pivoting on one dimension, all remaining dimensions are grouped together.

tip

Columns tries to detect dataset structure and suggest a suitable query automatically. Check the Keys section for advanced options such as Pivot All.

Filter​

Columns supports two types of filters:

  • Query filters: Applied before processing; they affect the final metric and dimension results.
  • In-graph filters: Interactive controls in the chart used to adjust the displayed view.
info

Do not confuse the two: query filters shape data before visualization, while in-graph filters help explore data after rendering.

Supported Query Filter Operations:​

Most operations align with standard SQL. Wildcards such as % can be used for pattern matching.

  1. = (equals): Field must equal a value
  2. != (not equals): Field must not equal a value
  3. IN: Field must match one of multiple values
  4. NOT IN: Field must not match any of the specified values
  5. IS EMPTY: Field is null or empty (for strings)
  6. IS NOT EMPTY: Opposite of above
  7. LIKE: Field matches a pattern (e.g., %value%)
  8. NOT LIKE: Field does not match a pattern
  9. ILIKE: Case-insensitive pattern match
  10. NOT ILIKE: Case-insensitive pattern mismatch