Azure Data Engineering - Learning Path

 Referred Link - https://www.linkedin.com/feed/update/urn:li:activity:7330431719021445121/

Download Sub Topics & Trainer Details - https://drive.google.com/file/d/1Cco1WUtKNGJSCpkC2ORgYnCs6N3p8laY/view?usp=drive_link 

1. SQL
→ Writing efficient queries, joins & indexing
→ Window functions & performance tuning
→ Working with stored procedures in Synapse

2. Python
→ Automating data processing workflows
→ Working with APIs & Azure SDKs
→ Data manipulation with Pandas & NumPy

3. PySpark
→ Handling big data with DataFrames & RDDs
→ Optimizing transformations & actions
→ Managing partitions for performance

4. Azure Data Factory (ADF)
→ Building ETL pipelines with Data Flows
→ Scheduling & triggering data movement
→ Debugging & monitoring pipeline failures

5. Azure Databricks
→ Working with notebooks, clusters & jobs
→ Optimizing Spark queries with caching & partitions
→ Connecting Databricks with ADF & Synapse

6. Azure Synapse Analytics
→ Dedicated vs. Serverless SQL Pools
→ Performance tuning & query optimization
→ Integrating Synapse with external data sources

7. Azure Data Lake Storage
→ ADLS Gen1 vs. Gen2 & when to use each
→ Managing storage security & access control
→ Optimizing file formats (Parquet, Delta, Avro)

8. Azure Key Vault
→ Securing secrets & credentials
→ Managing encryption for sensitive data
→ Implementing access control with RBAC

9. Microsoft Fabric
→ Understanding OneLake for unified storage
→ Using Data Factory within Fabric for ETL
→ Implementing end-to-end analytics solutions

Tags:

#LearningRoadmap, #FreshersLearning, #DataEngineering,