Being able to trust your data is critical for data intensive industries, but the ability to detect anomalies before they become a problem isn’t always enough. When a pipeline fails, teams need to know not only what was impacted, but also who can fix it and how. Without that ability, issues can spread, impacting dashboards, AI bots and reporting across the board as well as bringing in new compliance issues for the team to face.
Which is where this enhancement comes in.
Ataccama One has been updated with new versions of our Data Observability features, improving monitoring, alerts and a plethora of other features. While Ataccama has always included data observation functionality, we’ve worked to strengthen existing features and provide new ones to our users. Including focuses on improved alerting, impact analysis and monitoring. So issues can be found and resolved in a timely manner.
But why does this update matter to you?
Updated pipeline monitoring:
- Improved pipeline monitoring across a number of orchestrators
- Including dbt, Airflow, Dagster, Azure DataFactory and AWS Glue
- Detects failures and anomalies during the data transformation process
- Reuse data quality rules across pipelines and persisted datasets
Through updated pipeline monitoring, teams can troubleshoot issues early, and prevent downstream processes from being impacted by bad data. Saving your team time by providing clear visibility into what went wrong, why and how to fix it.
Enhanced alerting prioritization:
- Failure notifications routed through email, Slack or Microsoft Teams
- Prioritize alerts via custom context
- Including critical data elements, stewardship groups and business terms
Through improved alerting capabilities and prioritization, your team can be notified on the alerts that they care about most immediately. Strengthening your governance capabilities with your data and optimizing your operations overhead.
Increased impact analysis:
- Increased visibility into anomaly impact though technical analysis
Through the updated impact analysis, users are able to actively monitor the impact of issues on downstream reports and business impact. Ensuring users can make the best decisions on the most up to date data.
Resolution tracking and audit-ready history:
- Route work requests and assign ownership to tickets in Jira
- Coming soon to ServiceNow
Enabling your team to create conscious paper trails of changes made and by who, to ensure actions are taken and data trust is verified.
Benefits to you:
By combining Data Quality Gates with these new observability features, you and your team have the ability to notify, identify, and resolve any data issues quickly and efficiently. Utilizing active and customizable alerts, you can be notified of issues early and troubleshoot the problem at its source. We enable you to understand the exposure to bad data and minimize its impact on downstream services like dashboards and reporting. Alongside providing resolution tracking for clear audit trails, keeping you and your team well informed and within compliance regulations
Improve your team’s AI readiness and data governance while limiting the operational risk and manual overhead.
What’s Next?
As we continue to develop towards a vision of automated data trust, we’ll continue to provide updates and new features to the platform. So stay tuned for our product webinars and version updates as we strive to improve your data experience.
In the meantime, what part of this update impacts your team most?
We'd love to hear more about your specific data journey and what features you benefit from most or would like to see in the future.