Data quality monitoring for business intelligence developers
Detect data quality issues before the business sees incorrect numbers on dashboards
As a BI developer, you understand the importance of clean data for reliable dashboards. However, manually monitoring data quality can be time-consuming and distract from dashboard development and optimization. Inconsistencies in data quality can also lead to inaccurate insights and frustrated stakeholders.
DQOps platform proactively identifies issues before they disrupt your dashboards, giving you peace of mind and freeing you to focus on what matters most – building powerful BI solutions.
Data quality of the data model
The DQOps platform comes with more than 150 built-in checks that ensure typical data quality issues are detected. Once new tables are imported, DQOps automatically activates checks defined in data policies that focus on detecting anomalies, detecting schema changes, ensuring data freshness (timeliness), and identifying issues with table availability.
- Enable, disable, or customize the existing policies, and also add a new policy.
- Activate and run checks using a user-friendly interface.
- Review the results of the checks on data quality dashboards.
The DQOps platform comes with more than 150 built-in checks that ensure typical data quality issues are detected. Once new tables are imported, DQOps automatically activates checks defined in data policies that focus on detecting anomalies, detecting schema changes, ensuring data freshness (timeliness), and identifying issues with table availability.
- Enable, disable, or customize the existing policies, and also add a new policy.
- Activate and run checks using a user-friendly interface.
- Review the results of the checks on data quality dashboards.
No more missing data
No more missing data
Identify and address data quality issues impacting dashboards before the business raises an incident.
- 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
Receive alerts when there are issues in the initial data warehouse or data lake that could corrupt data mart tables before the dashboard refresh. Monitor data quality status on built-in data quality dashboards.
- Gain insights into potential issues and address them before they distort your visualizations.
- Prevent unnecessary dashboard refreshes if the underlying data is compromised.
- Ensure your users always have access to reliable information.
Receive alerts when there are issues in the initial data warehouse or data lake that could corrupt data mart tables before the dashboard refresh. Monitor data quality status on built-in data quality dashboards.
- Gain insights into potential issues and address them before they distort your visualizations.
- Prevent unnecessary dashboard refreshes if the underlying data is compromised.
- Ensure your users always have access to reliable information.
Dashboards always working
DQOps detects typical schema change issues such as missing, renamed, or reordered columns. An unexpected table schema change affects data pipelines and can also affect dashboards.
- Detect column schema changes that would make the dashboard fail to refresh.
- Get notified of table schema changes.
- Review recent table schema changes on built-in schema change data quality dashboards.
DQOps detects typical schema change issues such as missing, renamed, or reordered columns. An unexpected table schema change affects data pipelines and can also affect dashboards.
- Detect column schema changes that would make the dashboard fail to refresh.
- Get notified of table schema changes.
- Review recent table schema changes on built-in schema change data quality dashboards.