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Python Fundamentals for Data Engineering: SQL Server and SQLite

image image Project Description: Python Fundamentals for Data Engineering

This project aims to demonstrate fundamental data engineering skills using Python, SQL Server, and SQLite. The primary objective is to build a small ETL (Extract, Transform, Load) pipeline that showcases the essential steps of data engineering:

  1. Extract: Retrieve data from an SQL Server database using Python libraries.
  2. Transform and Clean: Process, clean, and transform the extracted data to ensure its quality and suitability for analysis. This includes handling missing values, correcting data types, and applying necessary transformations.
  3. Load: Load the cleaned and transformed data into a SQLite database for further use or analysis.

This project will highlight the integration of Python with SQL Server and SQLite, focusing on practical techniques for data extraction, transformation, and loading. By the end of this project, you'll have a foundational understanding of how to manage and manipulate data across different database systems using Python.

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