DP-600 cheat sheet

Fabric capacity SKUs run from F2 to F2048; F64 is roughly equivalent to Power BI Premium P1 and is the minimum capacity size that supports Copilot features.

Workspace roles are Admin, Member, Contributor, and Viewer; Contributor can create and edit items but cannot add users or change workspace permissions.

Deployment pipelines default to three stages (Development, Test, Production) and support up to ten; deployment rules rebind data sources or parameters per stage.

A workspace belongs to at most one domain; domains group workspaces for governance and may contain subdomains.

Endorsement levels are Promoted and Certified; Promoted can be set by any user with write permission on the item, while Certified requires a certifier designated by the tenant admin.

Git integration connects a workspace to an Azure DevOps repository and branch; supported item definitions are serialized to text for version control and ALM.

The Fabric Capacity Metrics app reports capacity unit (CU) consumption, throttling, and item-level usage, and must be installed once by a capacity admin.

Pausing a capacity stops compute charges and makes hosted items unavailable, while OneLake storage charges continue to accrue.

Sensitivity labels from Microsoft Purview propagate downstream, so a label applied to a lakehouse or warehouse carries through to reports built on it.

A lakehouse stores Delta tables and files accessed through Spark and a read-only SQL analytics endpoint; a warehouse provides full T-SQL read/write with no Spark engine.

Shortcuts are zero-copy references to internal OneLake paths or external ADLS Gen2, Amazon S3, Google Cloud Storage, or Dataverse locations; data stays in the source.

Dataflows Gen2 use Power Query Online and write results to a lakehouse, warehouse, or other destination; a pipeline can orchestrate their execution.

Medallion layers: bronze holds raw ingested data, silver holds validated and cleaned tables, and gold holds business-level aggregated tables for consumption.

V-Order is a write-time Parquet optimization that sorts and compresses Delta files for faster reads, especially in Direct Lake, and is enabled by default in Fabric.

OPTIMIZE compacts small Delta files; adding Z-ORDER BY a column co-locates related rows to improve file skipping on filtered queries.

VACUUM deletes Delta data files no longer referenced by the transaction log and older than the retention threshold, which defaults to 7 days.

Mirroring continuously replicates a source database into OneLake as read-only Delta tables with near-real-time latency and no read load on the source.

Copy activity with a staging lakehouse is recommended for large warehouse ingestion, and COPY INTO T-SQL provides high-throughput bulk loads.

Storage modes: Import copies data into memory, DirectQuery queries the source at run time, Dual can act as either, and Direct Lake reads Delta files in OneLake without a copy.

Direct Lake requires Delta Parquet tables (V-Order improves performance); when model guardrails are exceeded it falls back to DirectQuery unless fallback is disabled.

Row-level security roles are defined with DAX table filters; users are assigned by email or Microsoft Entra security group and can be tested with 'View as role'.

Object-level security hides tables or columns from a role and must be configured through the XMLA endpoint or Tabular Editor, not the Power BI Desktop UI.

Calculation groups bundle reusable calculation items applied to measures and are created with Tabular Editor or the XMLA endpoint.

Incremental refresh requires RangeStart and RangeEnd date/time parameters plus a policy that sets the store period, refresh period, and optional detect-changes column.

Measures are evaluated at query time and consume no model storage; calculated columns are computed during refresh and stored row by row in the model.

In a star schema, dimension tables relate one-to-many to fact tables; bidirectional cross-filtering is reserved for specific many-to-many or security patterns.

TMDL is the text-based tabular model definition language used for source control and ALM of semantic models in Fabric.

DAX query view runs EVALUATE statements against a semantic model and can create, update, or delete measures using DEFINE and UPDATE MEASURE syntax.

Visual calculations operate only on the visual's data; functions include RUNNINGSUM, MOVINGAVERAGE, RANK, COLLAPSE, and EXPAND, and model columns cannot be referenced directly.

Data Wrangler explores and transforms lakehouse data in an interactive grid and exports the equivalent PySpark code for reuse in a notebook.

The SQL analytics endpoint exposes lakehouse Delta tables as read-only T-SQL objects and supports views, inline table-valued functions, and stored procedures for access control.

A KQL queryset queries Real-Time Intelligence KQL databases using operators such as where, summarize, bin(), and render.

Quick measures generate DAX from templates such as aggregation, filter, and time intelligence, based on fields selected in a dialog.

Copilot in Power BI requires an F64 or P1-or-larger capacity plus a tenant setting, and can draft DAX, explain content, and summarize reports.

The Explore feature opens a semantic model in an ad-hoc canvas so users can build visuals from fields without editing the underlying report.

Spark notebooks in Fabric support %%pyspark, %%sql, %%scala, and %%r magic commands to switch the execution language per cell.