Hidden scope grows quietly.
Teams know they want Google Looker, but often cannot see the full Tableau, Power BI, MicroStrategy, Qlik, Domo, Cognos, or WebFOCUS estate they are really moving.
BI migrations to Google Looker
It’s 2026. Still doing BI migrations manually?
AI-powered Dashport cuts BI migration time, cost, and manual rebuild effort on the way to Google Looker. Human review and full parity checks stay where they matter.
TableauPower BIMicroStrategyQlikDomoCognosWebFOCUSTarget: Google Looker
Google Cloud Premier PartnerLooker Consulting Partner
AI-poweredRepeatable migration work moves through Dashport instead of manual rebuild alone.
ReviewedPeople stay in control where logic, exceptions, and rollout decisions matter.
ValidatedParity, data consistency, and signoff discipline are built into the path.
Why migrations stall
Manual BI migrations create work long before they create confidence.
Most BI migration programs stall for practical reasons: scope is harder to define than expected, manual rebuilds take multiple passes, and parity review across dashboards, metrics, and SQL-level logic arrives too late.
Manual recreation multiplies cost.
When every dashboard becomes a one-off rebuild exercise, delivery slows before governance even begins.
Late parity review creates rework.
Visual drift, metric drift, and broken report logic are usually discovered after too much build effort has already been committed.
Cutover starts to feel risky.
Business owners hesitate when the migration path does not show how trust will be protected before the switch.
48-hour assessment
Make the migration estate legible before the rebuild begins.
SquareShift starts with a 48-hour assessment to make the migration visible: what exists, what is repeatable, what needs manual review, and where cutover risk actually sits before the larger program begins.
It also separates what should move as-is, what should be simplified, what should be retired, and what should be rebuilt cleanly in Looker.
Surface the estate.
Workbooks, dashboards, reports, metrics, calculated fields, joins, filters, and dependencies.
Find repeatable work and edge cases.
Identify which tasks fit an AI-powered path and which assets still need controlled review.
Show blockers and migration waves.
Reveal effort signals, quick wins, dependency risks, and rollout order before rebuild work starts.
Turn ambiguity into decisions.
Clarify scope, parity exposure, manual-review flags, and the right path into Google Looker.
Dashport migration lifecycle and validation
Dashport stages the migration before cutover turns into business risk.
Dashport is the migration system behind the offer. SquareShift uses it to make scope visible, govern repeatable work, and bring assurance into the move before rollout starts.
Parity and validation
Parity is built into the path, not checked at the end.
SquareShift uses Dashport to accelerate repeatable work, then applies human review and migration governance where parity, business logic, and rollout discipline matter most.
Dashport supports pixel-perfect comparison where the move requires it, full visual and data parity across reports and logic, and absolute data consistency before rollout.
Use side-by-side comparison when exact visual replication matters to the migration decision.
Review dashboards, reports, metrics, filters, and SQL-level logic as one assurance model.
Hold rollout confidence to the underlying numbers, not just the screenshots.
Let automation handle repeatable migration work and keep manual review on complex edge cases.
Build confidence before the switch instead of hoping confidence appears after it.
Delivery experience
Migration continuity, scale, and Looker delivery expertise.
SquareShift brings the migration discipline to protect continuity, the delivery depth to handle scale, and the Looker expertise to make the target environment useful from day one.
Migration continuity
End-to-end Domo-to-Looker migration for a digital skilling platform serving 1.5M+ learners, with daily reporting continuity kept in view.
Read the case study Scale and modernizationSnowflake-to-BigQuery migration with existing Looker dashboards across 4B–5B events per week and 70+TB, with target-state dashboard performance under 10 seconds.
Read the case study Destination-state credibilityNear-real-time Looker and GCP reporting, including embedded reporting on the same page, so the destination stayed useful after migration.
Read the case studyGoogle Cloud Premier PartnerLooker Consulting Partner
Who this is for
Built for teams moving legacy BI into Google Looker.
If Tableau, Power BI, MicroStrategy, Qlik, Domo, Cognos, or WebFOCUS are in the way, Dashport gives you a faster, lower-cost move to Looker with AI-powered migration, full visual and data parity, and controlled approval where it matters.
You are moving from Tableau, Power BI, MicroStrategy, Qlik, Domo, Cognos, or WebFOCUS into Google Looker.
Dashport is built for legacy BI estates that need a faster path to continuity without a long manual rebuild.
You want to cut manual rebuild effort, migration cost, and delivery drag.
AI-powered migration handles the repeatable work so your team spends less time recreating dashboards by hand.
You need full visual and data parity before you switch business users to Looker.
Dashport brings side-by-side validation, metric checks, and SQL-level review into the migration path.
You want a controlled migration program, not another vague discovery cycle.
Start with a 48-hour assessment, sequence the work in waves, and move with explicit approval where it matters.
48-hour assessment
Get your 48-hour Dashport migration assessment.
Use the 48-hour assessment to turn the migration into a visible program. You see the estate, business-logic complexity, parity risk, manual review load, and the likely migration-wave path into Looker before the rebuild starts.
Migration estate, logic complexity, validation exposure, and rollout constraints.
A clearer inventory, clearer risk, and a clearer next decision.
One focused migration decision, then a governed path into Looker.
Start your 48-hour assessmentExplore Data, Analytics & BIOne path: assessment → governed migration plan → controlled Looker rollout.