The core principle is **Low-Code Lakehouse Data Ingestion**, a mechanism within data engineering that enables automated ETL (Extract, Transform, Load) workflows with minimal manual scripting by leveraging managed table constructs and structured copy activities. This concept operates under the rule of separating unprocessed raw assets from logical tables via intermediate process states to ensure idempotency and maintainable state transitions. The theoretical framework relies on **Managed Tables**, defined as database artifacts created directly from uploaded files without requiring complex schema definitions, which abstracts underlying storage complexity for users operating in cloud-native fabric environments. It belongs to the domain of Cloud Data Warehousing and relates to its parent discipline by democratizing data integration patterns traditionally reserved for senior engineers writing Python or Java pipelines.
The core principle is **Low-Code Lakehouse Data Ingestion**, a mechanism within data engineering that enables automated ETL (Extract, Transform, Load) workflows with minimal manual scripting by lever…