HOW OFTEN DOES A BUSINESS ASK YOU WHY THE DASHBOARD IS MISSING IMPORTANT INFORMATION?
Data Quality of the Data Model
Data Quality of the Data Model
Monitor the data quality of the tables you use for the dashboard. Verify that the data meets your needs.
DQO has a library of most important data quality checks. Enable our data quality rules like null checks, duplicate detection, invalid values detection or data integrity checks.
- Define your data quality requirements in code
- Profile your data sources and detect data quality issues
- Detect data integrity issues like missing dimension rows
No more missing data
No more missing data
Detect data quality issues that will affect the numbers on the dashboards before the business raises an incident.
DQO is a data quality monitoring platform. Define data quality requirements, and DQO monitors the data to detect when data quality requirements are not met. DQO sends an alert when there is a new data quality issue.
- Ensure that data quality requirements are always met
- Get alerts when dashboards show incorrect values
- Get alerts when source data has changed
Protection from the Data Warehouse downtime
Protection from the Data Warehouse downtime
Receive alerts when issues in the initial stages of a data warehouse or data lake corrupt the data mart tables that your dashboard is using before the data mart or your dashboard is refreshed.
Define the data lineage across all tables in the data pipeline. Receive alerts when upstream tables are affected by data quality issues that will later affect the tables that you are using in your dashboards.
- Learn about all data quality issues that can affect your dashboards
- Build a data lineage dependency tree to know how small changes can affect your dashboards
- Stop the dashboard refresh if the next refresh will corrupt the dashboard with invalid data
Dashboards always working
Dashboards always working
Detect data schema changes that will make your dashboard unusable because the column type or column format has changed in a way that will affect the dashboard.
DQO captures the column schema of the monitored tables. Table and column schemas are compared daily to detect changes. Define the expected format of text columns (codes) and important data ranges (numeric columns). DQO detects if all the rows meet your requirements.
- Define the requirements for data and field formats in one place
- Ensure that the rules for valid data ranges and field formats are always met
- Detect column schema changes that would make the dashboard fail to refresh
