Data Engineering Layers
Understanding the complete data lifecycle
Data engineering is organized into distinct layers, each solving specific problems in the data lifecycle. Click on any layer below to explore tools and concepts.
1
Data Sources
Where data originates and how to access it
Solves: Data accessibility, API integration, format standardization
Next: Data Ingestion
2
Data Ingestion
Moving data from sources to storage systems
Solves: Reliable transfer, quality validation, error handling
Next: Data Processing
3
Data Processing
Transforming raw data into valuable insights
Solves: Data transformation, business logic, performance
Next: Data Storage
4
Data Storage
Storing processed data for analysis and consumption
Solves: Scalable storage, query performance, governance
Next: Data Consumption
5
Data Consumption
Making data accessible to users and applications
Solves: Visualization, reporting, self-service access
Final: Explore Tools