Data quality terms, defined with SQL.
Short definitions of the terms behind data checks and alerts, from freshness to reconciliation. Each one comes with a query you can run on your own data.
Alert threshold: static, relative, and baseline
An alert threshold is the value a metric must cross before an alert fires.
glossaryData freshness: what it is and how to check it
Data freshness is how old the newest row in a table is, compared with how old it is allowed to be.
glossaryData incident: what it is and how it's handled
A data incident is a period when a dataset is late, missing, or wrong enough that someone downstream could make a bad decision from it.
glossaryData reconciliation check in SQL: compare two systems
A data reconciliation check compares the same measure in two places, such as a source database and a warehouse, and flags the difference.
glossaryNull rate: how to calculate and alert on it in SQL
Null rate is the percentage of rows where a column has no value.
glossaryWhat is a data SLA? SLA vs SLO vs SLI for data
A data SLA is an agreement between the team that produces a dataset and the people who rely on it, stating what they can expect, such as 'the revenue table is updated by 7am on 95 percent of days'.
glossaryWhat is a data validity check? Examples in SQL
A data validity check tests whether the values in a column are legal, not just present.
glossaryWhat is a volume check? Row count checks in SQL
A volume check tests whether a table received roughly the number of rows you expect for a period, usually a day or an hour.
glossaryWhat is data observability? A SQL-first definition
Data observability is the practice of watching your data itself, not just your pipelines, so you find out it is late, missing, or wrong before a dashboard user does.
glossaryWhat is metric monitoring? Threshold vs baseline
Metric monitoring is watching a business number, such as daily revenue or signups, and alerting when it moves in a way that looks wrong.
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