Understand the difference between schema-on-write (databases) and schema-on-read (data lakes). Learn when to use each, how the Lakehouse architecture combines both, and how this relates to real ADF/Synapse pipelines.
Schema-on-Write vs Schema-on-Read: When to Use a Database vs a Data Lake Read More »
Compare Parquet, CSV, and JSON file formats for data pipelines. Includes real file size benchmarks, query performance comparison, and clear recommendations for when to use each format.
Parquet vs CSV vs JSON: Choosing the Right File Format for Your Data Pipeline Read More »
Learn what Azure Data Factory is, how its 6 core components work together, when to use it, and how to get started. A complete beginner’s guide for aspiring data engineers.
What is Azure Data Factory? A Beginner’s Guide for Data Engineers Read More »
Prepare for your Azure Data Factory interview with 15 real questions and detailed answers. Covers pipelines, activities, metadata-driven patterns, incremental loading, error handling, triggers, and performance optimization.
Top 15 Azure Data Factory Interview Questions Every Data Engineer Should Know Read More »
Fix the most common Azure Data Factory and Synapse pipeline errors including BadRequest null, dataset function not valid, case sensitivity issues, permission errors, and more. Real solutions from production experience.
Common Azure Data Factory and Synapse Pipeline Errors: A Troubleshooting Guide Read More »
Build an incremental data loading pipeline in Azure Synapse using the watermark pattern. Copy only changed rows using config tables, delta queries, and stored procedures. Covers ID-based and date-based watermarks with real examples.
Incremental Data Loading in Azure Synapse: The Delta Copy Pattern with Watermark Tables Read More »
Build a metadata-driven pipeline in Azure Synapse Analytics with Parquet output and stored procedure audit logging. Track rows copied, duration, and errors for every table. Step-by-step guide with real-world examples.
Building a Metadata-Driven Pipeline in Azure Synapse Analytics with Audit Logging Read More »
Learn how to build a metadata-driven pipeline in Azure Data Factory using the Lookup, ForEach, and Copy pattern. Step-by-step guide with parameterized datasets, dynamic expressions, troubleshooting tips, and production best practices.
Building a Metadata-Driven Pipeline in Azure Data Factory: The Complete Guide Read More »
Learn how to build and deploy a production-ready REST API using Python FastAPI on AWS Lambda with API Gateway and DynamoDB. Step-by-step guide with real-world examples.
Building a REST API with Python FastAPI on AWS Lambda: A Complete Guide Read More »
