#shorts The self service VS Governance for Analytics

May 23, 2026Channel
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RADACAD
RADACAD

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Video Details

Published1 month ago
Duration2:28
Video IDyf-2Scs1mmY
Languageen
CategoryScience & Technology
PrivacyPublic
Made for KidsNo
Video TypeRegular Video

Performance Metrics

Views224
Likes6
Comments2
Engagement Rate3.57%
Likes per 100 views2.68
Comments per 1K views8.93

Description

Too much control kills analytics. Too little destroys trust. The sweet spot is in between — and most organizations miss it completely.In this short video, I share one of the five most common reasons analytics projects fail after 20+ years of consulting across dozens of organizations: the governance trap.When every analyst builds their own reports with their own logic and their own definitions, you end up with chaos. The revenue number in the finance report doesn't match the one in the sales report. Both were built differently. And the business loses trust in the entire analytics platform.But the opposite is just as dangerous. A fully centralized BI team with no self-service creates a bottleneck — reports take weeks, requirements change, and the business gives up.The answer? A deliberate balance: ✅ A central team that defines standards and shared models ✅ A certified semantic model as the single source of truth ✅ Self-service users who work within the standards — not around them ✅ Content certification so users know what to trust. This is not a tool problem. No amount of Power BI or Microsoft Fabric features will fix a governance gap.👉 Watch the full video (5 reasons, full breakdown): https://www.youtube.com/watch?v=IpIKigzGbDw 📖 Read the full article on RADACAD: https://radacad.com/why-analytics-projects-fail-five-reasons-from-20-years-of-consulting/🔔 Subscribe for weekly Power BI and Microsoft Fabric content.#PowerBI #MicrosoftFabric #DataGovernance #SelfServiceBI #BusinessIntelligence #AnalyticsStrategy #DataAnalytics #PowerBITips #DataEngineering #BIArchitecture #DataLeadership #AnalyticsFailure #PowerBIArchitecture #FabricAnalytics #DataStrategy

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