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bcastelino
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data-source-connector

Connect to various data sources and generate a normalized data-model.json.

1|Updated May 13, 2026
Search Tags:#data extraction#data model#Power BI#data source connector#BI integration
One-click install
npx skills add https://github.com/bcastelino/powerbi-dashboard-generator --skill data-source-connector
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-source-connector
Source: https://github.com/bcastelino/powerbi-dashboard-generator/tree/main/skills/data-source-connector
Command: npx skills add https://github.com/bcastelino/powerbi-dashboard-generator --skill data-source-connector

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires scripts/introspect_source.py, scripts/introspect_unsupported.py, scripts/introspect_excel.py, scripts/introspect_csv.py, scripts/introspect_parquet.py, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill connects to various data sources and generates a normalized data model, enabling seamless data integration and analysis.

Core Features & Use Cases

  • Source-Agnostic Adapter: Connects to SQL databases, cloud warehouses, Excel/CSV files, OData/REST APIs, and SharePoint lists.
  • Normalized Data Model: Outputs a normalized data-model.json for downstream processing.
  • Use Case: Automate the creation of a data model for a Power BI dashboard by connecting to an Excel file and extracting table structures and relationships.

Quick Start

Use the data-source-connector skill to connect to the Excel file 'sales.xlsx'.

Frequently Asked Questions about data-source-connector

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate a normalized data model from an Excel file for Power BI?▼

To generate a normalized data model from an Excel file for Power BI, you use this skill to connect to your spreadsheet and automatically extract table structures and relationships into a standardized JSON output.

What is the best way to connect to multiple data sources like SQL databases and OData APIs?▼

Connecting to multiple data sources like SQL databases, OData APIs, and cloud warehouses is handled by the source-agnostic adapter, which normalizes connections and generates a unified data model JSON file.

Does the data source connector require specific drivers to connect to a cloud warehouse?▼

Yes, connecting to a cloud warehouse or any external data source requires source-specific Python drivers and scripts to establish the connection and extract the normalized data model.

Can I use this skill to extract data structures from CSV and Parquet files?▼

Yes, you can extract data structures from CSV and Parquet files using dedicated Python scripts, which parse the files and output a normalized data model for downstream business intelligence integration.

What format does the automated data model generation output for BI integration?▼

Automated data model generation for BI integration outputs a normalized data-model.json file, capturing the extracted table structures and relationships for seamless downstream processing in tools like Power BI.

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