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Semantic link is a feature that allows you to establish a connection between Power BI datasets and Synapse Data Science in Microsoft Fabric.

The primary goals of semantic link are to facilitate data connectivity, enable the propagation of semantic information, and seamlessly integrate with established tools used by data scientists, such as notebooks.

Semantic link helps you to preserve domain knowledge about data semantics in a standardized way that can speed up data analysis and reduce errors.

Package (PyPi) | API reference documentation | Product documentation | Samples

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This package has been tested with Microsoft Fabric.

Getting started

Prerequisites

The functionalities for semantic link are split into multiple packages to allow for a modular installation. If you want to install only a subset of the semantic link functionalities, you can install the individual packages instead of the semantic-link meta-package. This can help solve dependency issues. The following are some of the available packages:

To install the semantic-link package in Microsoft Fabric, you have two options:

  • Install the SemPy Python library in your notebook kernel by executing this code in a notebook cell:

    %pip install semantic-link
    
  • Alternatively, you can add semantic link to your workspace libraries directly. For more information, see Install workspace libraries.

Key concepts

SemPy offers the following capabilitites:

  • Connectivity to Power BI
  • Connectivity through Power BI Spark native connector
  • Data augmentation with Power BI measures
  • Semantic propagation for pandas users
  • Built-in and custom semantic functions

Next steps

View our Samples

Release files for semantic-link 0.4.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for semantic-link 0.4.0
File Interpreter ABI Platform
semantic_link-0.4.0-py3-none-any.whl Python 3 none any Details

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