Found 25 repositories(showing 25)
This repository builds a complete Data Engineering project from scratch using Azure Data Factory, Azure SQL DB, Databricks, Unity Catalog, Delta Live Tables, Spark Streaming, PySpark, and Databricks Asset Bundles. It also covers dimensional modeling, SCDs, CI/CD, and real-world pipeline design.
This project aims to constantly fetch data from spotify API and provide analytics on various parameters.
chetnarathore10
This project demonstrates an **end-to-end data engineering pipeline** built on **Microsoft Azure** using Spotify data. The goal is to ingest raw data from the Spotify API, transform it using Spark, and create analytics-ready datasets following data engineering best practices.
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suyogtarvate2962
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harshavardhan9603
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Mustafamegahed20
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Kunal-Kumar-Das191049
Built an end-to-end data platform using Azure Data Factory, Databricks, Delta Live Tables, Unity Catalog, and CI/CD.
AmitJamshetty
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Sudhamshdonkala
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markanthony-analytics
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bhaveshharmalkar
Spotify Azure Data Engineering End To End Project
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Ranjithprasanth
Spotify end to end data engineering project using Azure cloud technologies
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swapniltake1
This project implements an end-to-end Azure Data Engineering pipeline using Spotify streaming data, with a primary focus on duplicate data handling and data quality optimization
saifu-777
End-to-end Azure Data Engineering project on Spotify data using Azure Data Factory, Azure Databricks (PySpark, Delta Lake, Autoloader) and Azure SQL, implementing medallion architecture, metadata‑driven pipelines, incremental loads and analytics‑ready dimensional models.
kirankumarnm
End-to-end Data Engineering project using Spotify data, featuring modern pipelines built with Azure and Databricks. Includes data ingestion, transformation, orchestration, streaming, CI/CD, and dimensional modeling with SCD implementation.
This project showcases an end-to-end data engineering pipeline on the Spotify dataset using Azure Databricks, Delta Lake, and Unity Catalog, enabling incremental ingestion, real-time processing, and analytics to reveal insights on listener behavior, top artists, and regional engagement.
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