Thought leadership
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April 3, 2025
Get AI Ready with Governance & Data Observability
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Data trust is hard to earn and easy to lose. Especially when the first person to notice something’s broken is a business stakeholder looking at a dashboard. By then, damage is already done.
In our recent webinar with DataGalaxy, we walked through how data observability and governance can work together to help teams catch issues early, keep systems aligned, and make data trustworthy before someone in marketing starts asking, “Why are all the numbers zero?”
We also heard real stories from real companies like Zoom and Society Insurance, and talked through what modern implementations look like, from tooling to team structure, and when to build vs. buy.
Watch the full conversation below.
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Resource
Monthly cost ($)
Number of resources
Time (months)
Total cost ($)
Software/Data engineer
$15,000
3
12
$540,000
Data analyst
$12,000
2
6
$144,000
Business analyst
$10,000
1
3
$30,000
Data/product manager
$20,000
2
6
$240,000
Total cost
$954,000
Role
Goals
Common needs
Data engineers
Overall data flow. Data is fresh and operating at full volume. Jobs are always running, so data outages don't impact downstream systems.
Freshness + volume
Monitoring
Schema change detection
Lineage monitoring
Monitoring
Schema change detection
Lineage monitoring
Data scientists
Specific datasets in great detail. Looking for outliers, duplication, and other—sometimes subtle—issues that could affect their analysis or machine learning models.
Freshness monitoringCompleteness monitoringDuplicate detectionOutlier detectionDistribution shift detectionDimensional slicing and dicing
Analytics engineers
Rapidly testing the changes they’re making within the data model. Move fast and not break things—without spending hours writing tons of pipeline tests.
Lineage monitoringETL blue/green testing
Business intelligence analysts
The business impact of data. Understand where they should spend their time digging in, and when they have a red herring caused by a data pipeline problem.
Integration with analytics toolsAnomaly detectionCustom business metricsDimensional slicing and dicing
Other stakeholders
Data reliability. Customers and stakeholders don’t want data issues to bog them down, delay deadlines, or provide inaccurate information.
Integration with analytics toolsReporting and insights
Get the Best of Data Leadership
Subscribe to the Data Leaders Digest for exclusive content on data reliability, observability, and leadership from top industry experts.
Stay Informed
Sign up for the Data Leaders Digest and get the latest trends, insights, and strategies in data management delivered straight to your inbox.
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