Build a complete on-premises to Azure data pipeline using Self-Hosted Integration Runtime. Covers VM setup with SQL Server, SHIR installation, linked services, metadata-driven Copy pipeline, architecture diagrams, high availability, and production best practices.
Building an On-Premises to Azure Data Pipeline with Self-Hosted Integration Runtime Read More »
Complete guide to CI/CD for ADF and Synapse using Azure DevOps. Covers Azure Repos setup, connecting ADF/Synapse to DevOps, YAML pipelines, multi-stage deployments, pre/post scripts, approval gates, variable groups, branch policies, and enterprise patterns.
Master all three ADF trigger types. Schedule triggers for fixed-time runs, Tumbling Window for guaranteed time-series processing with backfill, and Event-Based triggers for file-driven pipelines. Includes setup steps, comparison table, and common patterns.
Complete guide to Azure SQL Database for data engineers. Covers service tiers, DTU vs vCore, authentication methods, Managed Identity, firewall rules, stored procedures, temporal tables, pipeline integration, and cost optimization.
Azure SQL Database for Data Engineers: Setup, Configuration, and Pipeline Integration Read More »
Master AWS S3 for data engineering. Covers buckets, storage classes, IAM policies, encryption, lifecycle rules, data lake patterns, boto3 Python SDK, S3 event notifications, and performance optimization.
AWS S3 for Data Engineers: Buckets, Storage Classes, IAM, and Data Lake Patterns Read More »
Master SQL CTEs and subqueries. Learn when to use each, how to chain multiple CTEs, recursive CTEs for hierarchies, deduplication patterns, and real-world data engineering examples.
SQL CTEs and Subqueries Explained: When to Use Each and Why CTEs Win Read More »
Prepare for data engineering interviews with 20 essential questions covering pipeline design, data modeling, ETL vs ELT, star schema, SCD, batch vs streaming, data quality, PII handling, and orchestration.
Top 20 Data Engineering Interview Questions: Concepts Every Candidate Must Know Read More »
The Python skills data engineers actually use: reading files (CSV, JSON, Parquet), pandas DataFrames, database connections, REST APIs, AWS/Azure SDKs, logging, error handling, and production ETL patterns.
Python for Data Engineers: The Essential Skills You Actually Use Every Day Read More »
Master every SQL join type with visual diagrams and real examples. Covers INNER, LEFT, RIGHT, FULL OUTER, CROSS, and SELF joins, plus ON vs WHERE, CTEs with joins, performance tips, and interview questions.
SQL Joins Explained: INNER, LEFT, RIGHT, FULL, CROSS, and SELF Joins with Real Examples Read More »
Master SQL window functions with real examples. Covers ROW_NUMBER, RANK, DENSE_RANK, NTILE, LAG, LEAD, running totals, moving averages, frame clauses, and the most common interview questions.
SQL Window Functions Explained: ROW_NUMBER, RANK, DENSE_RANK, LAG, LEAD, and More Read More »
