The full argument for each dashboard type lives in A Guide to the Six Types of Data Quality Dashboards. This page maps those six types onto a Microsoft shop: tables in SQL Server, Azure SQL, Synapse, or Fabric, and reports in Power BI. The question is the same one the guide asks first: who is your customer for this data?
The six dashboards on a SQL Server and Power BI stack
| Dashboard | Who it’s for | Built from | Where it lives |
|---|---|---|---|
| 1. Dimension-focused | Governance team, CDO | Scores broken down by Quality Dimension | TestGen scorecard |
| 2. Critical Data Element | Compliance, risk, finance | CDE score from columns flagged in the Data Catalog | TestGen scorecard |
| 3. Business goal-focused | Executives, budget holders | Scores by Business Domain, next to the business metric | Power BI report you build |
| 4. Data source-focused | Data engineers, vendor managers | Scores by Data Source or Source System | TestGen scorecard |
| 5. Data consumer-focused | Analysts, Power BI report owners | Scores per Data Product or Stakeholder Group | TestGen scorecard |
| 6. Ticket-driven workflow | Data quality leads, engineering managers | Failed tests turned into issue reports and work items | Jira or your ticket system |
TestGen’s scorecards and their breakdown categories come from the Quality Scores and Data Catalog docs, checked November 2026. Most teams run more than one of these, because each audience wants a different cut of the same data.
Build every dashboard on test results
The guide’s test results equivalence principle decides whether any of the six works: every number on a dashboard should trace to a failing test, and every failing test should become a ticket somebody can fix. Once the fix lands, the same test proves it on the next run.
That rules out the shortcut most Power BI authors reach for. Power Query’s data profiling tools show column quality, distribution, and statistics, but over the first 1,000 rows by default, and only inside the editor. A completeness percentage from a profile tells you a number moved. It doesn’t tell you which rows, which rule, or who should fix it.
TestGen’s score is built the other way. Per its Quality Scores page, the overall score is the profiling score (from hygiene issues found during data profiling) multiplied by the testing score (from test failures), recalculated after every run. Dismiss an issue and it stops counting. Click any row in a score breakdown and you get the hygiene issues and test failures behind it.
What each dashboard looks like in a Microsoft shop
1. Dimension-focused
For governance teams that report against completeness, accuracy, consistency, timeliness, uniqueness, and validity. TestGen breaks any scorecard down by those six quality dimensions, so this one exists as soon as you have a profiling run and a test run. It’s a good broad brush and a poor motivator: pair it with one of the narrower views.
2. Critical Data Element
For compliance, risk, and finance, especially where a regulator names the fields. Flag CDEs in TestGen’s Data Catalog by hand, in bulk, by CSV import, or with automatic detection during data profiling, and the scorecard shows a CDE score computed only from those columns, next to the total.
3. Business goal-focused
For executives and whoever funds the work. This is the one that belongs in Power BI, because the business metric it sits next to (revenue, fulfillment rate, a launch target) is already there. Tag tables with a Business Domain in TestGen so scores roll up the way the business is organized, then put that score beside the KPI it affects.
4. Data source-focused
For data engineers and the people who manage vendors and upstream systems. Tag tables in the Data Catalog with Data Source or Source System, and a scorecard ranks them by the quality they deliver. The guide’s caveat holds: you can measure a supplier without being able to make them care, so the scorecard is evidence for a conversation, not the fix.
5. Data consumer-focused
For analysts, data scientists, and the owners of specific Power BI reports. Tag the tables behind a report with a Data Product or Stakeholder Group, then save a scorecard filtered to that tag, so a report owner sees only the data their report reads. Expect requests for one per team, and keep them as saved filters rather than separate builds.
6. Ticket-driven workflow
For data quality leads who need to show remediation progress. TestGen produces the tickets’ raw material: a PDF issue report per failed test with sample rows and the SQL behind it, and notifications that post to Microsoft Teams or feed a Jira Cloud automation rule that creates work items. The dashboard of tickets opened and closed lives in your ticket system. It measures work done, not data quality, so run it alongside one of the scorecards.
Where Power BI fits
TestGen’s docs, checked November 2026, don’t describe a Power BI connector, so this page doesn’t claim one. They do document two ways to get results out. The REST API returns run summaries, a run’s individual test results, and a project’s quality score rollup with an optional breakdown. The Test Results page and the Data Catalog export to Excel. Power BI reads both through its standard Web and Excel connectors, so either can sit under a report.
In practice that means the business goal view, and any consumer view you want inside the report it protects, are the ones worth building in Power BI. The dimension, CDE, and source scorecards already exist in TestGen.
Supported Microsoft sources and cost
TestGen connects to SQL Server 2019 and later with a SQL login, Azure SQL Database, Azure Synapse, and Microsoft Fabric Lakehouse and Warehouse through the SQL analytics endpoint. It reads only, runs its queries inside your database, and is self-hosted on a server you choose. The core is open source under Apache 2.0. Enterprise is $100 per user per month plus $100 per connection per month. Start from the Microsoft install page.
For the walk-through on video, watch A Guide to the Six Types of Data Quality Dashboards and the follow-up masterclass, which builds all six in TestGen.
Documentation: Quality Scores, Explore and Create Scorecards, View Score Details, Data Catalog, Investigate Test Results, Notifications, API.