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Key concepts overview

These topics introduce the basic concepts of DQO.

  • Checks

    Description of the check. A test for data quality which is a combination of a data quality sensor and a data quality rule.

  • Sensors

    Description of the sensors. A template SQL query that captures metrics.

  • Rules

    Description of the rules. A set of conditions against which sensor readouts are verified, described by a list of thresholds.

  • Data quality KPIs

    Description of data quality KPIs. The results of data quality measurements calculated as a percentage of passed data quality checks for each table, database, or connection.

  • Data quality dashboards

    Overview of data quality dashboards. Built-in dashboards for displaying data quality KPI.

  • Data quality dimensions

    Introduction to data quality dimensions. Dimension are aspects of data that can be measured and through which its quality can be quantified.

  • Data stream segmentation

    Description of data stream segmentation. Data stream is a group of rows that were loaded from a single or different sources and aggregated into one table.

  • Data storage

    Description how data is stored in DQO.

  • Working with the YAML files

    Introduction to working with YAML configuration files in DQO.

  • Working with CLI

    Introduction to working with DQO Command-Line Interface.