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Section 1
Task 1.1: Perform data ingestion
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Preview: Data Ingestion and Transformation (34%)
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- 0 overview segment
- 3 core concepts
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Core Concepts
- Choose ingestion from arrival pattern, latency, ordering, replay, scale, durability, and consumer requirements—not from service familiarity.
- Kinesis Data Streams supports multiple independent consumers. Standard consumers share per-shard read throughput; enhanced fan-out provides dedicated consumer read throughput.
- Partition keys determine shard routing and per-key ordering. More consumers do not mean records are 'stolen' from other independent applications.
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Section 2
Task 1.2: Transform and process data
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Section 3
Task 1.3: Orchestrate data pipelines
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Section 4
Task 1.4: Apply programming concepts
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Section 5
Task 2.1: Choose a data store
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Section 6
Task 2.2: Understand data cataloging systems
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Section 7
Task 2.3: Manage the lifecycle of data
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Section 8
Task 2.4: Design data models and schema evolution
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Section 9
Task 3.1: Automate data processing by using AWS services
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Section 10
Task 3.2: Analyze data by using AWS services
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Section 11
Task 3.3: Maintain and monitor data pipelines
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Section 12
Task 3.4: Ensure data quality
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Section 13
Task 4.1: Apply authentication mechanisms
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Section 14
Task 4.2: Apply authorization mechanisms
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Section 15
Task 4.3: Ensure data encryption and masking
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Section 16
Task 4.4: Prepare logs for audit
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Section 17
Task 4.5: Understand data privacy and governance
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