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azuresynapse

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This project builds an End-to-End Azure Data Engineering Pipeline, performing ETL and Analytics Reporting on the AdventureWorks2022LT Database.

  • Updated Jan 24, 2024
  • Jupyter Notebook

Ingested Tokyo Olympic data into Azure Data Lake using Azure Data Factory. Enhanced data quality with Apache Spark on Azure Databricks. Optimized SQL queries on Synapse Analytics, reducing execution time. Developed engaging Power BI dashboards, boosting user engagement creating KPI's with DAX.

  • Updated Mar 5, 2024
  • Jupyter Notebook

This project leverages Azure Cloud services like Azure Data Factory, Azure Databricks, and Synapse Analytics to execute a data engineering workflow. Utilizing data sourced from the Olympic API on GitHub, it involves extracting raw data into Azure Data Lake Storage, transforming it with PySpark on Azure Databricks, and analyzing the transformed data

  • Updated Mar 10, 2024
  • Jupyter Notebook

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