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📊 ETL Pipeline Automation

Built a comprehensive Extract, Transform, Load pipeline with Python, APIs, SQL and Power BI visualization for minimizing technical involvement with data processing and analytics.

Project Overview

This project involves fetching data from a sql table using python fastapi, transforming it using pandas and loading it in excel sheet. The processed data is then visualized in Power BI template for reporting and insights.

Key Objectives

Technologies Used

Python
FastAPI
SQL
Pandas
Power BI
Excel

Implementation Details

Extract Phase

Developed Python fastAPIs to fetch data from sql table using custom optimised queries.

Transform Phase

Used Pandas for data manipulation and transformation. Applied data validation rules, cleaned inconsistencies, and standardized formats across all data sources.

Load Phase

loading the data in excel format to get the processed results

Power BI Visualization

Created interactive dashboards in Power BI to visualize the processed data and provide actionable insights.

Key Results & Achievements

Pipeline Success

99.8% Reliability

Non technicality

no technical involvement

Processing Time

40% Faster

Data Quality

99.5% Accuracy

Key Features

Data Validation

Built comprehensive validation rules to check data quality, detect anomalies, and handle edge cases before loading to production database.

Power BI Integration

Created direct Power BI to excel connection to the processed data for real-time dashboards and reporting capabilities.

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