All Monitor Templates
Here is the list of all the Sifflet Monitor Templates:
| Monitor template | Category | Application | Description |
|---|---|---|---|
| Volume | Table-level Health | Table | Counts newly ingested rows and alerts on anomalous behaviour |
| Row-level Duplicates | Table-level Health | Table | Computes the duplication rate [%] on a row-level and compares it to the expected value based on past behavior. |
| Freshness | Table-level Health | Table | Verifies whether new rows have been ingested into your table following the expected pattern. |
| Freshness (Update time gap) | Table-level Health | Table | The monitor fails when the duration since the last update deviates from historical norms. |
| Schema Change | Table-level Health | Table | Detects any change to the schema: new field(s), removed field(s), existing field(s) with updated types or names. |
| Metrics | Metrics | Fields: Numeric | The monitor detects changes in an aggregated metric of a field (i.e. Sum) |
| Custom Metrics | Metrics | Table | The rule fails if the time series returned by the query behaves differently from how it did in the past |
| Correlated Metrics | Metrics | Fields: Numeric | The monitor fails if defined metrics diverge significantly from one another. |
| Distribution Change | Field profiling | Fields: All | The monitor fails if the distribution of a given field has changed abnormally compared to a previous run. |
| Duplicates | Field profiling | Fields: All | The monitor detects anomalies regarding the count of duplicates for a column or a set of columns |
| Unique | Field profiling | Fields: All | A simplified version of the duplicates monitor that fails if a column or set of columns is not unique |
| Nulls | Field profiling | Fields: All | The monitor detects anomalies regarding the count of nulls/empties in a column or a set of columns |
| Value List Validation | Field profiling | Fields: String | The monitor fails if the chosen field has values that are not present in the given list. |
| Value Range | Field Profiling | Fields: Numeric | The monitor fails if the chosen field has any values outside of a given range. |
| Referential Integrity | Field profiling | Fields: All | The monitor fails if values in one table are not present in the other table |
| Is an email | Format validation | Fields: String | The monitor fails if the chosen field contains at least one row that does not have an email format. |
| Is a phone number | Format validation | Fields: String | The monitor fails if the chosen field contains at least one row that does not have a phone number format. I.e. checking for 6 to 16 digits and will accept the field to contain the following characters +, -, (, ) |
| Is UUID | Format validation | Fields: String | The monitor fails if the chosen field contains at least one row that does not have a UUID format. |
| Matches regex | Format validation | Fields: String | The rule fails if the selected field contains at least one row that does not match the format specified by the given regular expression. |
| SQL | Custom | Table | An advanced template to write custom monitors based on business specifics. The SQL query must describe a quality breach on one or more tables within the same data source. |
| No Code Conditions | Custom | Table | As for SQL, this template allows writing custom monitors based on business use cases. With conditional statements, no SQL syntax is needed. The rule fails if values are found inside the filtering criteria set by conditional rules. |
| SQL Conditions | Custom | Table | This template is similar to the SQL monitor template but instead of specifying the entire SQL query, only the condition (boolean) needs to be specified. This way, you can use complex SQL conditions while benefiting from the added features from Sifflet such as Incremental Scans, Look-back period, etc. |
Updated 20 days ago
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