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Seven AI agents build each Power BI semantic model and its report pages from the MicroStrategy metadata, and a consultant reviews the result: about an hour per validated model, down from one to two days by hand.
One report through the pipeline
Each metric's formula is read as text from the MicroStrategy metadata, so measure logic comes straight from the source definition.
Fields are mapped to your data platform views, and missing views are listed before modelling starts.
A documented Power BI semantic model and its report pages.
Every rendered page is compared with a screenshot of the MicroStrategy original and sent back until it matches.
A consultant reviews each model, and a person confirms which source reports merge into one Power BI report.
At an international online lottery operator that beat its MicroStrategy licence deadline, with 738 reports in scope
Your MicroStrategy licence or support date sets the deadline, and the build pace decides whether you make it. The lottery operator had three months before the tool went dark, with the migration 40% complete against a plan of 80 to 90%.
MicroStrategy holds no tabular model to lift across, so every Power BI model is designed from what the report shows. By hand, that took one to two days per report, and adding people does not compress it.
At the lottery operator several reports were specified against Snowflake views that did not exist yet. Each one stopped a manual build halfway and cost a round trip to the client's team.
Assessment: two to six weeks, as part of the migration
Usage logs decide the scope, so reports nobody opens are retired before the build. You get the project plan, the reports to rebuild with their business owners, a source data inventory with risks, and a fixed price.
Pipeline build
We build a few reports by hand first to set the rules, and the agents build the rest: semantic models and report pages. They propose which source reports merge into one Power BI report, and a person confirms it before anything is built, because a wrong split leaves you maintaining duplicates for years. Data gaps go to your team as one list.
Acceptance
Each report is signed off against its MicroStrategy original, page by page.
Adoption
Tenant and governance setup, a deployment pipeline for the report lifecycle, usage tracking, an admin toolkit and training.
Several hundred structurally similar reports on a stable data platform, where only the reporting tool on top changes.
Reports with heavy bespoke logic or unusual layouts stay closer to a manual build and gain less. In the lottery estate they were the minority.
The same pipeline shape holds for Cognos, Business Objects, Qlik or Tableau; only the source-analysis agent changes.
The operator beat its licence deadline once the agent pipeline replaced the report-by-report build. The 50 reports built by hand first gave the agents their rules and made the other 688 cheap, and the consultant moved from building models to reviewing them. Read the case study →
We also run MicroStrategy platforms: administration, security, deployments and performance. MicroStrategy managed services →
The same team builds the data platform underneath: Snowflake, Databricks, BigQuery or Microsoft Fabric.
They gain less. Reports with heavy bespoke logic or unusual layouts stay closer to a manual build; on simple reports, which were most of the lottery estate, the pipeline removes around 80% of the build effort.
No. The data platform stays where it is and only the reporting tool on top of it changes. In the lottery case Snowflake kept its place: the client owned the Snowflake transformations, and we owned the MicroStrategy analysis and the Power BI build.
The pipeline marks every unresolved field and you get one precise list while it is still cheap to fix. At the lottery operator, one Finance report needed five Snowflake views and three did not exist yet; the client's team built them while the pipeline carried on with other reports.
No. The pipeline runs under a flat-rate coding-agent subscription, so volume never turns into a metered token bill. A Fabric capacity is needed only at the end, to publish the finished reports into a workspace.
Only metadata: report definitions, metric formulas and the names of the data platform views. Report data stays where it is.
We tell you roughly how many of your reports the pipeline can take, which kinds stay manual, and what the assessment covers: the first two to six weeks of the migration. You speak with Michał Dębski, co-founder and solution architect.
