Collibra Community

Good morning! I have a form which I have developed in Workfow Developer and some of the fields are drop downs with more than 20 values. Rather than hard-code all of the values, is there a way to get the form to pull the allowable values from the values that are listed for the attribute itself? I hate having to put them in both places. Thanks

We are trying to establish a best practice for governing patient questionnaires and responses.  For example, the PHQ-9, GAD-7, and the Medicare Annual Wellness assessment.  The responses to individual questions are aggregated and reported widely, so we want to define those and make sure to document the calculation(s). We also want to make sure we have assets that document the questionnaires themselves.  Specifically: Do others include a separate measure in the Collibra Glossary for each question on each assessment?  For example, the PHQ-9 has 9 questions and a total score.  Would it be best practice to create 10 measures? We currently use a business term asset type for the assessments themselves.  Would others recommend including all of the questions in the definition? We have heard a recommendation to use a separate asset type for assessments/Questionnaires, does anyone have experience with that?  

Hello all we have just started using Collibra and want to be able to report on DQ results (Metrics) that we gather in various other DQ tools, such as Databricks and IBM CP4D. we have defined several data Quality Rules, but now want to start capturing the metrics associated with each of these over time. I see in the rule I can put rows loaded and passing fraction, but this is only once. how do I load them in on a daily basis, so that we can track progress. What Asset Type should I use to load the metrics into? how do I get to see them right now I get the errors: No data quality monitors yet. (when viewing from the rule) something went wrong (when viewing from a data product) any help or advice would be greatly appreciated please? Will

Here at Oregon Health and Science University (OHSU) in Portland Or, we use the Collibra Data Intelligence Platform in support of our Data Governance efforts. Rather than having our institution refer to our portal as Collibra, we've branded it as the Analytics Marketplace . As some additional context: Our Data Governance Office (DGO) reports up through our Chief Data Officer who is also responsible for leading our centralized analytics division. At the current time our Marketplace includes a business glossary, along with enterprise catalogs of reports, KPIs and metrics, self-service reporting data sets, trainings, and policies and standards. If you have a DG portal at your institution what have you decided to call it? Thanks, Brent

Hi everyone, My organization set up a connection to our Tableau Server and we are currently ingesting a majority of Tableau assets including workbooks and dashboards. However, the only thing we are not seeing are the Tableau Prep Flows available on our Tableau Server. Reading through the Collibra Documentation around Setting Up Tableau, I do not find any information how this asset type can be ingested. Are Tableau Prep Flows just not supported or am I missing a step in our connection setup? This is the only document where I can see what tableau assets can be ingested, but no mention of prep flows. Any information would be greatly appreciated. Thank you, Fatima

As data leaders, we’re all feeling it. Data is no longer just powering dashboards and reports — it’s fueling AI assistants, automated decisions, regulatory reporting, and mission-critical business processes. The expectation? Instant. Trusted. Context-rich answers. But the reality can feel different. Fragmented governance. Missing business context. Manual quality checks. Unclear ownership. Teams spend more time searching for and validating data than actually using it to drive the business forward. That’s where data products come in. 🚀 New Solution Brief: Deliver ROI with Data Products is here. This resource walks through how data products help organizations deliver discoverable, trustworthy data at scale — while clearly demonstrating measurable ROI. You’ll learn how Collibra’s framework and adoption journey enable you to: Build an integrated internal data marketplace Guide teams through a flexible data product build experience Use AI to map technical data to business context Automate data quality checks and policy compliance Implement data contracts with embedded service-level objectives Apply a unified control layer for secure access and masking The goal isn’t just more data — it’s trusted data, accessible at scale, driving real business impact. 👉 Access the solution brief here. As always, would love to hear from our community. How are you approaching data products today? Where are you seeing the biggest wins (or friction)? Let’s keep learning from one another.