Load Excel, JSON, CSV, Parquet, and XML data into SQL databases.
npx skills add https://github.com/saajunaid/junai --skill data-loader
Please help me install this Agent Skill. Skill: data-loader Source: https://github.com/saajunaid/junai/tree/main/.github/skills/data/data-loader Command: npx skills add https://github.com/saajunaid/junai --skill data-loader
Load data from Excel, JSON, CSV and other formats into relational databases with built-in validation, transformation, and error handling to reduce manual data-entry effort and improve data quality.
Load a provided data file into your configured database, perform basic validation, and report any invalid records.
High-intent search queries and answers about installing and using this skill.
To load CSV and Excel files into a SQL database, this Skill automates data discovery, schema inference, validation, and batch loading into SQL Server, PostgreSQL, MySQL, and SQLite using pandas and SQLAlchemy connectors.
Yes, you can validate and transform JSON data before inserting it into PostgreSQL. The pipeline applies configurable data transformation and validation rules prior to batch loading to ensure reliable data integration.
The best way to migrate Parquet data into MySQL is using an ETL pipeline with built-in error handling. This Skill uses pyarrow and pymysql to read Parquet files and reliably load them into your target database.
Yes, this data loading approach supports XML files and SQLite databases. It identifies and loads data from XML formats into SQLite, applying transformation and validation to ensure data quality during ingestion.
To perform ETL data ingestion from multiple file formats, this Skill automates the discovery of Excel, JSON, CSV, Parquet, and XML sources, applying schema inference and batch loading into a unified staging area.
To load Excel exports into a SQL Server database, the process utilizes pandas, openpyxl, xlrd for file parsing, and pyodbc with SQLAlchemy for the database connection and reliable batch loading.
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