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Have you ever wondered what Data Engineering really means? 🤔
This visual makes it finally clear and simple! 💡

Data Engineering is all about how data moves — from where it’s created to where it becomes useful for business, AI, and analytics.

Here’s the full breakdown 👇

🔹 Data Sources:
Data comes from different places — APIs, records, and files.

🔹 Data Ingestion:
This is where the data is collected — either in real-time (streaming) or in batches.

🔹 Data Processing:
Once collected, data is cleaned, transformed, and prepared for analysis using data pipelines and machine learning tools.

🔹 Data Storage:
All this processed data is stored in systems like a Data Warehouse or Lakehouse for easy access.

🔹 Data Consumers:
Now, this organized data is used by Data Scientists, Analysts, and Business Intelligence tools to make decisions.

🔹 Data Governance:
Ensures data quality, catalogs, and consistency using lineage, glossary, and marketplaces.

🔹 Data Infrastructure:
The backbone — including memory, networking, and storage that keeps everything running smoothly.

🔹 Data Security:
Keeps data safe using access controls, backups, and IAM (Identity Access Management).

In short — this image explains the entire data journey from raw information to meaningful insights! 🚀
If you’re a beginner in Data Engineering, Data Science, or AI, this is the easiest way to understand the big picture. 💾✨


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