Every Power BI consultant knows the scenario: you've built a polished report for one client, and now a second client wants something similar but pointing at their own data. The report structure is the same, the DAX logic is the same — only the datasource is different.
So you copy the .pbix, open it, and start manually updating every table reference, every measure, every filter. Hours of tedious, error-prone work.
There has to be a better way. And there is.
The datasource switching problem
When you change a Power BI report's datasource, it's not just one connection string. A typical report has:
- Tables that need to point at different source tables
- Columns that may have different names in the new dataset
- DAX measures containing hardcoded table and column references
- Visual queries in PBIR JSON files referencing specific entities
- Filters at the visual, page, and report level
- Bookmarks that store filter state snapshots
Change one and miss another, and you get broken visuals, missing data, or subtle calculation errors that are hard to catch.
The manual approach (and why it fails at scale)
The traditional approach is:
- Duplicate the report
- Update the data source connection
- Fix every broken reference manually
- Test every page
This works for one report. But if you're a consultancy that builds templated reports — one for retail, one for healthcare, one for logistics — and each client gets a customised version, you're doing this dozens of times a year. Mistakes are inevitable.
Dummy BI Automate automates exactly this. See how it works
How Dummy BI Automate handles it
Dummy BI Automate uses a 6-phase wizard that reads your PBIP project folder (or converts a .pbix file automatically) and systematically rewrites everything:
Phase 1: Base Column Mappings
Map each source table's columns to their new equivalents. The tool reads your TMDL model files and shows you every table and column in the semantic model, suggesting matches based on name similarity.
Phase 2: Table Mappings (Calculated + Manual Tables)
Map calculated tables and manually-entered tables that reference base columns from Phase 1.
Phase 3: Measure Mappings
Map measures that reference specific tables or columns. The tool parses DAX expressions to find all references and rewrites them.
Phase 4: Parameters & Groups
Map calculation group items (common in time intelligence patterns) and field parameters (used in dynamic visuals where users switch which measure is displayed).
Phase 5: Validation
The tool validates the mappings before applying — checking that all references are resolved and no orphaned dependencies remain.
Phase 6: Apply
Rewrites all affected files in one operation.
After mapping, the tool rewrites:
- All TMDL files (model definition, table definitions, relationships, M expressions)
- All DAX expressions (measures, calculated columns, calculated tables)
- All PBIR JSON files (visual queries, filters, bookmarks, drillthrough parameters)
For example: Client A has a Sales table from SQL Server with a Revenue column. Client B has the same table from Snowflake, but the column is called TotalRevenue. The wizard maps Sales.Revenue → Sales.TotalRevenue and rewrites every DAX measure, filter, and visual query that references it.
The entire process takes minutes, not hours. And because it's systematic, nothing gets missed.
Why local processing matters
Your Power BI data often contains sensitive business information — revenue figures, customer data, employee records. Dummy BI Automate processes everything on your local machine. Your datasource mappings, your TMDL files, your DAX expressions — none of it leaves your computer.
This isn't a marketing angle. It's an architectural decision. The tool reads files from your filesystem and writes files to your filesystem. There is no cloud service, no upload step, no API call that carries your data.
Getting started
- Save your Power BI report in PBIP format (File → Save As → Power BI Project) — or point the tool at a
.pbixfile directly - Open Dummy BI Automate
- Select your project folder
- Run the Switch Datasource wizard
- Map your tables, columns, and measures
- Apply — and you have a switched report ready to open in Power BI Desktop
If you're a consultant or a team that builds repeatable Power BI solutions, datasource switching automation saves measurable time on every engagement.