Azure End-To-End Data Engineering Project (From Scratch!)

Azure Data Engineering End-To-End Project | Azure Data Factory | Databricks | Pyspark | Azure Synapse Anlaytics

In this video, I take you through End-to-End Data Engineering project from scratch where I leverage powerful technologies like Azure Data Factory, Azure Data Lake, Databricks, Azure Synapse Analytics, and Apache Spark.

🔍 What You’ll Learn:
- How to design and implement a robust data pipeline using Azure Data Factory.
- The process of data integration and transformation with Databricks.
- Utilizing Azure Synapse Analytics for efficient data warehousing and analytics.
- Best practices for handling big data solutions and real-time data processing with Apache Spark.
- And some Azure Data Engineer Interview Questions

Data Source Link : https://github.com/anshlamba03/Adventure-Works-Data-Engineering-Project/tree/main/Data
Spark & Synapse Script : https://github.com/anshlamba03/Adventure-Works-Data-Engineering-Project/tree/main/Reference%20Script
Azure Portal Account : https://portal.azure.com/
Original Dataset Link : https://www.kaggle.com/datasets/ukveteran/adventure-works?

Timestamps
0:00 Introduction
1:52 Data Architecture
10:43 Azure Free Account
15:07 Data Understanding (API)
18:41 Data Ingestion (Bronze Layer)
19:01 Creating Azure Resources
34:49 Azure Data Factory Overview
37:27 Azure Data Lake Gen2
40:37 ETL Pipelines with Azure Data Factory
1:01:16 Real-Time Scenarios with ADF
1:39:03 Azure Databricks Resource
1:44:20 Databricks Cluster & Overview
1:51:55 Service Principle
2:02:00 Data Transformation with Databricks
2:09:01 Apache Spark (Silver Layer)
2:30:20 Pyspark Tutorial
3:09:26 Big Data Analytics with Pyspark
3:19:08 Azure Synapse Analytics (Gold Layer)
3:52:58 Openrowset() function
4:06:17 External Tables in Synapse Analytics
4:29:02 Integrate Data Warehouse with PBI



Connect with ME - https://www.linkedin.com/in/ansh-lamba-793681184/



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