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azuredatalakegen2

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The data engineering project aims to migrate a company's on-premises database to Azure, leveraging Azure Data Factory for data ingestion, transformation, and storage. The project will implement a three-stage storage strategy, consisting of bronze, silver, and gold data layers (Medalion architecture). Documentation of the project is in PDF file.

  • Updated Mar 4, 2024
  • Python

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

Integration of Covid-19 data utilising Azure Data Factory to perform data ingestion, transformation and storage activities. The goal of this guided project was to become familiar with Microsoft Azure technologies, including; Azure Data Factory(ADF), Azure Data Lake Storage Gen2, Azure SQL Database, Azure Blob Storage, Dataflow, Databricks, etc.

  • Updated Jan 13, 2023
  • Python

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