🧰Power Query

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Also known as: Power Query Editor, Get & Transform

A data preparation tool and engine in Power BI and Excel for discovering, connecting, and transforming data.

DESCRIPTION

Power Query is Microsoft’s data preparation technology embedded in Power BI, Excel, and other services. It provides a visual editor and the M formula language to connect to diverse sources, clean and shape data, and produce repeatable transformations. Query folding pushes supported operations to source systems for performance. Power Query is also the foundation for Power BI Dataflows, enabling centralized, reusable ETL in the cloud. Typical tasks include merging tables, filtering rows, pivoting/unpivoting, and type conversions. It is widely used for self-service ETL and complements SQL- or code-first approaches.

ALTERNATIVE DEFINITIONS

Microsoft Support

Power Query is a data connection technology that enables you to discover, connect, combine, and refine data across a wide variety of sources.

Emphasizes data connection and end-to-end preparation steps within Excel.

Source

Microsoft Learn

Power Query provides fast, easy data gathering and shaping capabilities.

Highlights ease-of-use and shaping capabilities for self-service ETL.

Source

RELATED TERMS

M Query Query Folding Power BI Dataflow Extract-Transform-Load Merge Append Parameters Data Types in Programming Transformation

COMPETING TERMS

dbt

RELATIONS

• Broader: Query

KNOWLEDGE AREAS

Data Engineering Data Integration & Interoperability Data Warehousing & BI Programming Languages

TARGET AUDIENCE

BI Specialist Data Analyst Analytics Engineer Data Engineer

EXTERNAL SOURCES

• Wikipedia - Power Query
• Microsoft Learn - Official Power Query documentation hub
• Microsoft Learn - Editor UI reference and features
• SQLBI - Tutorials and guidance for Power Query
• Microsoft Learn - Connector list and capabilities

TOP QUESTIONS

Why is Power Query important for analytics?

It enables robust, repeatable data preparation directly in BI tools, reducing reliance on external ETL and empowering analysts with self-service transformations.

Category: Relevancy

What are common Power Query mistakes?

Breaking query folding, overusing row-by-row operations, and not documenting steps can degrade performance and maintainability.

Category: Mistakes

How does Power Query relate to Dataflows?

Dataflows use the Power Query engine to run transformations in the service, enabling shared, reusable ETL across workspaces.

Category: Example

Is Power Query an ETL or ELT tool?

It can be both, but often functions as ELT when transformations fold to the source, and ETL when executing locally before loading.

Category: Opinion

What performance features matter in Power Query?

Query folding, source-side indexes, careful type changes, and using Merge with keyed joins are critical for speed.

Category: Requirements

How does Power Query compare to dbt?

Power Query is GUI-driven and user-friendly; dbt is SQL-first with software-engineering workflows, better for centralized, code-managed ELT.

Category: Alternatives

What is a hot topic around Power Query?

Leveraging Power BI Dataflows for governed, reusable transformations and pushing more logic via query folding.

Category: Topic

Where should beginners start with Power Query?

Begin with basic transforms: filter, split columns, merge tables; then learn query folding and parameters for robust pipelines.

Category: Tutorial

How is Power Query managed in enterprises?

Teams standardize transformation patterns, review folding, centralize shared logic in dataflows, and document steps and data lineage.

Category: Management