Click-the-button works for short-lived deployments with simple dashboards. For anything you will live with for years, the semantic-layer-first rebuild costs less in month six and dramatically less in year two when 50 Power BI semantic models would otherwise have diverged.
Decision support (2-3 weeks), semantic model + RLS design (4-6 weeks), wave 1 migration of top 20% of dashboards by traffic (4-8 weeks), wave 2 (6-12 weeks), long-tail retirement (4-8 weeks). Total 5-9 months for a 100-300 dashboard environment.
RLS gets rebuilt as Power BI roles tied to a certified attribute model, not converted by an automated tool. LOD expressions become DAX measures with explicit grain logic. Both are the parts automated tools cannot do well.
Yes. We have helped clients NOT migrate as often as we have helped them migrate. The Audit is decision support, not a migration sales motion.
Banks, credit unions, and capital markets. Microsoft 365 is the operating system, Azure / Fabric is the data stack, ALCO and credit-risk dashboards rebuild cleanly in Power BI semantic models.
P&C, life, and health carriers. Premium capacity for underwriting and actuarial workloads, NAIC reporting on Power BI, Fabric for claims-data ingestion.
Hospital systems and payers running Epic on top of Azure. Direct Lake mode over OneLake, HIPAA-aware Power BI semantic models for clinical and operational reporting.
Federal and state agencies on Azure Government. Power BI for citizen-facing reporting and internal audit-ready dashboards, Fabric for FOIA-compliant data foundation.
Universities and academic medical centers. IPEDS and student-success reporting in Power BI, Fabric capacity for research and administrative analytics.
Discrete and process manufacturers. OEE and shop-floor telemetry through Fabric Real-Time Intelligence, Power BI dashboards over Synapse and Azure SQL.
Independent assessment of whether migration is the right call. Target architecture (Power BI Premium vs Fabric vs hybrid). License + capacity math. 1-page recommendation with NO option included. 2-3 weeks.
Star schema, role-playing dimensions, RLS roles, certified measure definitions. Output is a deployable Power BI dataset and a governance document. 4-6 weeks.
Top 20% of dashboards by traffic. Built on the certified semantic model. Parallel run validation. Business sign-off per dashboard. 4-8 weeks.
The rest of the high-value dashboards. Mix of manual rebuild and automated-tool-assisted conversion where appropriate. 6-12 weeks.
Automated tools used aggressively here because the long tail by definition is low-stakes. Anything that the automated pass cannot handle gets retired instead of rebuilt. 4-8 weeks.
If Microsoft is co-funding the pilot, we help you scope it so the pilot informs the decision instead of forcing it. We also know when to take the pilot and when to walk away.
Tableau Cloud migrations, Power BI rebuilds, and the structured approach in between. We pattern-match faster because we have lived both ends.
Most migration vendors convert dashboards. We rebuild the semantic model first, then connect dashboards to it. Year-two cost is half.
Many Tableau deployments do not need to migrate. If modernization on Tableau is the right call, we say so on the discovery call.
We know the F-sku math and the Premium capacity math at your user count. The license decision is real money.
The source platform expertise , we modernize Tableau when migration is the wrong call.
Metric certification before migration starts. The work that prevents 50 divergent semantic models.
Tableau to Power BI migration services. Structured semantic-layer-first rebuild, Pulse Convert evaluation, ECIF / FastTrack navigation, RLS + LOD translation. Honest about NO migration when that is the right call.
Structured semantic-layer-first migration. Honest about NO migration when modernization is right.
Tableau to Power BI migration consulting is the engagement-based work of moving a Tableau deployment to Power BI (or Power BI on Microsoft Fabric) without losing the semantic model, row-level security, or end-user trust. We ship the structured rebuild by default and use automated tools (Pulse Convert, others) only where they actually fit.
ECIF / Microsoft FastTrack navigation when Microsoft is co-funding.
A click-the-button conversion. We use automated tools selectively, not as the strategy.
A migration sales motion. We have helped clients NOT migrate as often as we have helped them migrate.
An open-ended retainer. Engagements are scoped in waves with go / no-go gates.
Recreating every Tableau workbook as-is moves the sprawl onto a new tool. Here is how a rationalized migration differs.
Categorized by complexity and rebuilt to fit Power BI, not pixel-copied.
Every workbook recreated as-is, including the ones nobody uses.
Rationalized first, so you rebuild what matters, not the whole estate.
Calculations re-expressed correctly in DAX and tested against fixtures.
Parallel run with numbers reconciled against Tableau before cutover.
The work concentrates in complex dashboards and DAX translation, which is why rationalizing the estate first pays back. These are the factors that move the effort.
Migrations tier dashboards: simple operational views rebuild fast, while complex, calculation-heavy workbooks take far more. Rationalizing first removes the ones nobody uses.
Tableau calculations do not map one-to-one to DAX; the more custom logic, the more translation and testing.
Reconnecting sources, gateways, and refresh schedules in the Power BI service adds work.
Running both platforms while numbers are reconciled is the safeguard that prevents production surprises.
Tableau authors need Power BI enablement so the new estate is actually used.
The licensing math usually favors Power BI over time, but the migration cost lives in complex dashboards and DAX, so scope is measured before any number is discussed.
You are standardizing on Microsoft and want to consolidate licensing.
You have a large Tableau estate that needs rationalizing, not pixel-copying.
You want validated, reconciled reports, not a risky lift-and-shift.
You want Tableau fixed and governed, not replaced: see Tableau Consulting.
The numbers disagree by definition: start with Semantic Layer Engineering.
You want managed Tableau operations instead: see Tableau Server Managed Services.
Pulse Convert claims 88% accuracy. The 12% gap is where the migration cost actually lives. We ship the semantic-layer-first rebuild that costs less in month six and a lot less in year two, AND we tell you when not to migrate at all.
Tableau to Power BI migration moves a Tableau deployment to Power BI without losing the semantic model, row-level security, or user trust. Automated converters claim high accuracy, but the gap is where the cost lives. Thinklytics ships a semantic-layer-first rebuild that costs less in year two, and tells you when not to migrate at all.
The migration economics work best in industries where Microsoft 365 and Azure are the existing operating system and the dashboards-to-rebuild fall inside the 70th percentile of complexity. These are the segments where our migration audits land most often.
Start with a 30-day Truth Audit. We map your dashboard inventory, the semantic-model debt, the RLS reality, and the license / capacity math. Output is a wave plan and a fixed-price proposal , or a recommendation NOT to migrate.