Bigeye, the creators of the leading data observability platform, today announced the release of Dashboard and Issues — a pair of integrated features that create a complete data quality workflow from a holistic understanding of the state of data quality to a smarter way to resolve issues.
Bigeye enables data teams to detect and proactively resolve data quality and pipeline issues before the business is affected. The latest release puts even more tools into the hands of data teams. Dashboard gives data team leaders a high-level view of data health, making it simple to monitor data quality coverage, impact on SLAs, time to resolution, and other key analytics. Underpinning the insights that Dashboard provides are Issues. Issues make it easier than ever for data engineers and analysts to dig in and resolve data quality issues.
Dashboard: Dashboard provides a single view of the most important information about a company’s data quality. From surfacing the most pressing data quality issues to highlighting opportunities to improve monitoring coverage, Dashboard gives everyone – from data engineers to executives – a deeper understanding of the state of the health of the company’s data and how it’s improving over time. Dashboard enables data teams to better understand data quality with:
- Priority lists: Ranked lists of datasets and SLAs help data teams focus their efforts on the highest priority data.
- Health trends: Trend graphs quickly summarize the reliability of the data, and how it’s changing over time.
- Coverage levels: Indicators show where monitoring coverage is good, and where it can be improved.
- Progress reporting: Metrics from Issues make it easy to report the impact from your team identifying and resolving problems.
Issues: Fueling the insights captured in Dashboard, Issues enables data teams to resolve data quality issues faster and more effectively by threading data quality alerts into a single timeline with valuable context on related issues, past remediation, and the current status of the issue. Issues can be accessed from anywhere in the Bigeye platform, including the catalog or when viewing an SLA, making it easy to document past fixes and speed up future resolution. Issues help data teams more effectively resolve data quality issues with:
- Threaded notifications: Alerts related to the same metric are aggregated into a single Issue.
- Faster resolution: Manage Issues — acknowledge, resolve, and close — with a single click.
- Smarter alerts: Mark alerts as good or bad to help improve anomaly detection over time.
- Swifter action: Leave notes and context on closed Issues to help your team resolve similar issues faster the next time.
“With Bigeye, we have created a powerful data observability platform that enables data teams at companies like Instacart, Clubhouse, and Udacity to create more reliable data applications and support thousands of users with trusted data. We’re excited to build more intelligence into our data observability platform to give customers even more tools to understand the health of their data and resolve issues fast,” said Egor Gryaznov, CTO and co-founder, at Bigeye.
To learn more about how Dashboard and Issues work together to provide data teams with an end-to-end understanding of the health of their data, read the Bigeye blog.
Bigeye enables data teams to proactively resolve data quality and pipelines issues before the business is affected – enabling them to scale increasingly complex data platforms with the reliability the business demands. Customers are able to proactively address data quality and pipeline issues before the business is affected. Powering Bigeye’s data observability platform are the ability to automatically instrument their data with more than 60 pre-built data quality metrics, continuous monitoring, and advanced anomaly detection that dynamically adapts to changes in the business.
About Bigeye
Bigeye is a data observability platform that brings data engineers, analysts, scientists, and stakeholders together to build trust in data. Companies like Instacart, Clubhouse, and Udacity use Bigeye to automate monitoring and anomaly detection and create SLAs to ensure data quality and reliable data pipelines. With complete API access, a user-friendly interface, and automated yet flexible customization, data teams can monitor quality, proactively detect and resolve issues, and ensure that every user can rely on the data. www.bigeye.com
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