Скачать или смотреть Data Engineering Explained | From ETL to Cloud Pipelines (Real-World View)

In this video, we explain data engineering the way it actually works in real projects.

This is not a tool-based tutorial or a certification-focused explanation.
Instead, we follow the real evolution of data engineering — from traditional ETL and on-prem systems to modern cloud-native and big data platforms.

We explore how data engineers transform raw transactional data into reliable, analytics-ready datasets that power reporting, dashboards, and AI systems.

You will learn:
• What data engineering really means in enterprise environments
• How ETL evolved from stored procedures and SSIS to cloud pipelines
• How OLTP data is transformed into OLAP systems for analytics
• The role of data warehouses, data lakes, and lakehouse architectures
• Why data engineering became critical after cloud and big data
• How data engineers create real business value from raw data

This video is especially useful for:
• Aspiring data engineers
• SQL Server, SSIS, and ETL developers
• Cloud data professionals
• BI and analytics engineers
• Anyone working with large-scale data pipelines

Subscribe to “Data and AI with Varath” for real-world data engineering, architecture, and analytics content.

Chapters:
00:00 - Data Engineering
00:27 - Why Data Engineering Became Critical
00:53 - What Data Engineering Really Does
01:11 - The Evolution of ETL
02:08 - From OLTP to OLAP
02:43 - Data Warehouse, Data Lake, and Lakehouse
03:12 - Modern Data Engineering Pipelines
03:29 - Mendelian Architecture
03:49 - Why Data Engineering Matters