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Topic Cram Sheet621 words

Cram Sheet — Design data integration

AZ-305 › Unit 2 › Design data integration

Cram Sheet — Design data integration

Separate movement, orchestration, transformation, streaming, and business workflow requirements. Use this sheet after the linked lessons: it is a retrieval map and decision aid, not a substitute for the worked examples.

Cram target

Unit
2
Blueprint domain
Design data storage solutions
Decision anchors
4
Mastery standard
Recommend and reject

Decision matrix

Requirement shapeStart withQualifying rule
Batch movement/orchestrationData Factory in Microsoft Fabric or Azure Data FactoryUse pipelines, connectors, and an appropriate integration runtime
Large transformationsFabric Spark/dataflows or Azure DatabricksMatch engineering model and operating ownership
High-throughput event ingestionEvent HubsPartition for throughput and consumer independence
Business/SaaS workflowLogic AppsUse connectors, state, approvals, and B2B integration

The phrase start with matters. A default is only defensible after checking all hard constraints: region and SKU support, protocols, scale, availability, security, residency, recovery, skills, and operating ownership. When two rows appear in one scenario, compose them rather than forcing one service to solve every concern.

Fast design method

  1. Name the workload boundary and the users or systems that cross it.
  2. Extract measurable requirements: latency, throughput, volume, RTO/RPO, consistency, outage window, and retention.
  3. Mark security and governance constraints: identity, network reachability, encryption, residency, audit, and separation of duties.
  4. Select the simplest viable default from the matrix.
  5. Test it against failure domains, scale transitions, deployment, monitoring, and cost.
  6. State the nearest alternative and the one constraint that makes it weaker.
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Figure 1 — Mermaid diagram

Text equivalent: derive requirements, choose a default, qualify it against constraints, add operational and failure behaviour, then explain the trade-off.

Answer the architecture decision

For design data integration, begin with this lens: Separate movement, orchestration, transformation, streaming, and business workflow requirements.

High-value traps

  • A connector list is not an integration architecture.
  • Event Hubs is not a work queue.
  • Integration runtime placement controls network reachability.

Scenario rehearsal

An organisation asks for the capability described by the first matrix row, but also adds a strict recovery target, private connectivity, and a small operations team. Write a recommendation that identifies the core service, the supporting continuity and network controls, and the operating trade-off. Then reject the nearest service alternative using one explicit requirement. If your answer lists products without a traffic, data, identity, or recovery flow, it is incomplete.

Final-minute checklist

  • I can distinguish every service in the matrix by requirement, not logo or name.
  • I know which controls operate at identity, management, data, and network planes.
  • I check regional/SKU support and current limits when a scenario depends on them.
  • I include monitoring, health, capacity, recovery, and ownership in the recommendation.
  • I can explain why the strongest distractor fails.
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Source and freshness

Aligned to the current AZ-305 study guide, the attached Exam Ref, and the attached AZ-305 study guide corpus. Current Microsoft Learn documentation controls product availability, limits, and renamed services. Reviewed 2026-08-02.

All Designing Microsoft Azure Infrastructure Solutions (AZ-305) Study Resources

Related Notes

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Loading Diagram...
Flowchart, left to right. Scenario connects to Requirements. R connects to Default service family. D connects to All hard constraints met?. F connects to Choose qualified alternative (No). F connects to Add operations and failure handling (Yes). A connects to O. O connects to Explain trade-off.

Design data integration checkpoint

Card 1 of 4

Front of flashcard 1 of 4

For batch movement/orchestration, what is the default decision anchor?

easy

Data Factory in Microsoft Fabric or Azure Data Factory: Use pipelines, connectors, and an appropriate integration runtime.

az-305retrieval

Design data integration checkpoint

Card 1

Front

For batch movement/orchestration, what is the default decision anchor?

Back

Data Factory in Microsoft Fabric or Azure Data Factory: Use pipelines, connectors, and an appropriate integration runtime.

Card 2

Front

For large transformations, what is the default decision anchor?

Back

Fabric Spark/dataflows or Azure Databricks: Match engineering model and operating ownership.

Card 3

Front

For high-throughput event ingestion, what is the default decision anchor?

Back

Event Hubs: Partition for throughput and consumer independence.

Card 4

Front

For business/saas workflow, what is the default decision anchor?

Back

Logic Apps: Use connectors, state, approvals, and B2B integration.

Design data integration checkpoint

Card 1

Front

For batch movement/orchestration, what is the default decision anchor?

Back

Data Factory in Microsoft Fabric or Azure Data Factory: Use pipelines, connectors, and an appropriate integration runtime.

Card 2

Front

For large transformations, what is the default decision anchor?

Back

Fabric Spark/dataflows or Azure Databricks: Match engineering model and operating ownership.

Card 3

Front

For high-throughput event ingestion, what is the default decision anchor?

Back

Event Hubs: Partition for throughput and consumer independence.

Card 4

Front

For business/saas workflow, what is the default decision anchor?

Back

Logic Apps: Use connectors, state, approvals, and B2B integration.