Microsoft Power BI Desktop turns data from spreadsheets, databases, online services, and other connectors into a local analytical model and an interactive report. The work happens in stages. Power Query cleans and reshapes source data, the model joins tables and holds calculations, and report pages present the result through charts, tables, slicers, and maps. A report can remain a local file or move to the Power BI service for browser access and sharing.
Shape the source
Power Query Editor records each cleanup operation as a step. A query can remove columns, split text, change data types, merge tables, or group rows before loading the result. The recorded sequence makes a transformation repeatable when the source refreshes. It also means that an early change can break later steps. Renaming a source column, for example, can leave a later selection step looking for a name that no longer exists.
Microsoft Power BI Desktop separates a simple worksheet import from importing an Excel workbook that already contains Power Query queries or a Power Pivot model. Existing measures, calculated columns, and relationships can move into the Power BI model, but workbook presentation does not become an identical report page. The user still needs to inspect types, refresh results, and rebuild visual layout where necessary.
Model filter paths
Relationships let a selection in one table filter rows in another. A typical sales model places unique customer or product keys on the one side and repeated transaction keys on the many side. Microsoft Power BI Desktop can detect some relationships, but uncertainty leaves them for the modeler to create.
A relationship does not repair the underlying data. Duplicate values on a column meant to be the one side can stop refresh, and blank or mismatched keys can produce an unexpected blank member in a visual. Dates can also appear equal while hidden time values prevent a match. These errors often look like a chart problem even though the fault sits in the model.
Bi-directional filtering can solve a specific interaction, but applying it widely creates more paths for a filter to travel. Microsoft warns that this can reduce performance or make a relationship path ambiguous. A single, deliberate direction is easier to reason about in most star-shaped models.
Choose data storage
Import mode copies data into the local model. Reports respond quickly because visuals read the compressed model, but new source records appear only after refresh. DirectQuery leaves the records at the source and sends queries as a visual needs them. That keeps the report closer to current source data, while shifting more responsibility to the database, network, credentials, and query design.
A DirectQuery report that feels acceptable against a small test table can slow down when filters generate expensive source queries. Schema changes at the source can also require a Desktop refresh before the field list catches up. Microsoft Power BI Desktop supports mixed storage designs, but combining imported and remote tables adds relationship and refresh behavior that needs testing rather than assumption.
Publish with boundaries
Publishing sends the report and its semantic model to a selected workspace. This is a deployment step, not two-way synchronization. If someone edits visuals in the browser, those edits do not return to the original Desktop file. Republishing from the local file can replace the workspace model and report, so teams need to decide which copy owns future design changes.
On-premises sources may need a gateway before scheduled refresh or DirectQuery works in the service. Permissions also move from a personal editing context to workspace and data-source identities. A successful local refresh therefore does not prove that the published report can reach the same data. Microsoft Power BI Desktop is strongest when the query, model, report, and deployment stages receive separate checks.
