This lesson develops Data Ingestion, Storage Formats, NoSQL Models, and Data Lake Design within Oracle Big Data Fundamentals Ed 2.
The activity is anchored to a data platform team evaluating how high-volume clickstream, device, and transaction data should be ingested, stored, processed, governed, and served for analytics, keeping every implementation, analysis, administration, or support decision specific to this course.
Demonstrate batch and streaming ingestion patterns, connectors, queues, and landing zones within a data platform team evaluating how high-volume clickstream, device, and transaction data should be ingested, stored, processed, governed, and served for analytics, then capture the exact configuration, command, transaction, report, trace, or code evidence that proves the expected result.
Implement a controlled workshop covering structured, semi-structured, and unstructured formats; compression and partitioning and key-value, document, column-family, and graph modeling concepts, then test a failure, exception, or business-control scenario involving data lake zones, metadata, retention, schema evolution, and quality controls.
The Data Ingestion, Storage Formats, NoSQL Models, and Data Lake Design result must be reproducible, traceable to approved inputs, and consistent with expected Oracle product or business-process behavior.
Diagnose issues in batch and streaming ingestion patterns, connectors, queues, and landing zones, structured, semi-structured, and unstructured formats; compression and partitioning, key-value, document, column-family, and graph modeling concepts, or data lake zones, metadata, retention, schema evolution, and quality controls without making an unverified production change.
Learners isolate the smallest proven cause, apply a reversible correction, rerun validation, and record the preventive action.
Complete a validated implementation or analysis for Data Ingestion, Storage Formats, NoSQL Models, and Data Lake Design and defend the result with documented evidence.