Audience

Businesses that need a data transformation and data preparation engine to improve their data analysis and decision-making

About Microsoft Power Query

Power Query is the easiest way to connect, extract, transform and load data from a wide range of sources. Power Query is a data transformation and data preparation engine. Power Query comes with a graphical interface for getting data from sources and a Power Query Editor for applying transformations. Because the engine is available in many products and services, the destination where the data will be stored depends on where Power Query was used. Using Power Query, you can perform the extract, transform, and load (ETL) processing of data. Microsoft’s Data Connectivity and Data Preparation technology that lets you seamlessly access data stored in hundreds of sources and reshape it to fit your needs—all with an easy to use, engaging, no-code experience. Power Query supports hundreds of data sources with built-in connectors, generic interfaces (such as REST APIs, ODBC, OLE, DB and OData) and the Power Query SDK to build your own connectors.

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Integrations

API:
Yes, Microsoft Power Query offers API access
See Integrations

Ratings/Reviews

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Company Information

Microsoft
Founded: 1975
United States
powerquery.microsoft.com/en-us/

Videos and Screen Captures

Microsoft Power Query Screenshot 1
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Product Details

Platforms Supported
Cloud
Windows
Mac
Training
Documentation
Support
Online

Microsoft Power Query Frequently Asked Questions

Q: What kinds of users and organization types does Microsoft Power Query work with?
Q: What languages does Microsoft Power Query support in their product?
Q: What kind of support options does Microsoft Power Query offer?
Q: What other applications or services does Microsoft Power Query integrate with?
Q: Does Microsoft Power Query have an API?
Q: What type of training does Microsoft Power Query provide?

Microsoft Power Query Product Features

Data Preparation

Data Access
Data Blending
Data Mashup
Data Transformation
Data Modeling
Visual User Interface
Collaboration Tools
Data Governance
Machine Learning
Data Cleansing

ETL

Data Analysis
Match & Merge
Data Filtering
Data Quality Control
Metadata Management
Version Control
Non-Relational Transformations
Job Scheduling