> ## Documentation Index > Fetch the complete documentation index at: https://docs.dqlabs.ai/llms.txt > Use this file to discover all available pages before exploring further. # Overview > What Frequency metrics are in Prizm — measure how often specific values, lengths, and ranges appear in a column to catch format and enum violations. ## What is a Frequency metric? Frequency metrics measure **how often specific values, lengths, and value ranges appear** in a column. They expose broken enumerations, boundary violations, and distribution shifts that generic completeness or uniqueness checks do not catch. **Type:** Configurable — Frequency metrics are part of the Structural (Advanced) profile. They are enabled per column through the Configure Structural Metrics panel. Frequency metrics answer the question: *Are the values in each column conforming to their expected set and boundaries?* ### Metrics | Metric | Level | Description | | ------------------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Min Length | Attribute | Minimum string length observed across all values in the column | | Max Length | Attribute | Maximum string length observed across all values in the column | | Length | Attribute | Distribution of string lengths — tracks how lengths vary across all values | | Length Range | Attribute | The span between Min Length and Max Length — alerts when the range widens unexpectedly | | Min Value | Attribute | Minimum numeric or date value observed in the column | | Max Value | Attribute | Maximum numeric or date value observed in the column | | Value Range | Attribute | The span between Min Value and Max Value — flags out-of-bounds values and unexpected range changes | | Enum | Attribute | Frequency distribution of distinct values — the count of each unique value observed, particularly useful for low-cardinality columns (status codes, categories) | | Regular Expressions | Attribute | User-defined regex patterns evaluated against column values. Tracks the percentage of values that match a given expression over time | ### How frequency monitoring works Prizm captures the value, length, and range distributions on each profiling run. Baselines are learned automatically. Alerts fire when new values appear in previously stable enumerations, when length distributions shift significantly, or when the proportion of out-of-range values crosses a configured threshold. For Regular Expressions, the user supplies one or more regex patterns. Prizm evaluates each pattern against the column and records the match rate per run. Alerts fire when the match rate drops below a configured threshold. ### Example use cases **Detecting a new order status:** An e-commerce platform introduces a new fulfillment status `"SPLIT_SHIPMENT"`. The Enum metric on `orders.status` fires an alert the first time this value appears — before any downstream order-processing pipeline has been updated to handle it. **Phone number format validation:** A `phone_number` column should always match the pattern `^\+[0-9]{10,15}$`. A Regular Expressions metric with this pattern alerts when a batch of records loaded without the country code prefix, dropping the match rate from 100% to 73%. The Enum metric is most powerful for low-cardinality columns (fewer than \~50 distinct values). For columns with high cardinality (like free-text fields), use Distribution metrics instead. Enable Frequency metrics per column, configure regex patterns, set thresholds, and manage alerts.