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Implementing Data Engineering Solutions Using Azure Databricks

Topic 1

Question 13

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A data engineering team is designing the serving layer of a Unity Catalog `analytics` schema. For each of the following requirements, choose the most appropriate Unity Catalog object. Assume Databricks SQL with serverless compute is available and that materialized views can be created and refreshed standalone. ```mermaid flowchart TD subgraph Req1[Requirement 1] R1[Store raw ingested transaction rows that downstream jobs run INSERT, UPDATE, DELETE, and MERGE INTO against] O1{Object: managed table / view / materialized view} end subgraph Req2[Requirement 2] R2[Expose a column-renamed, business-friendly projection of a table with NO extra storage and results that are always live at query time] O2{Object: managed table / view / materialized view} end subgraph Req3[Requirement 3] R3[Precompute an expensive GROUP BY aggregation so a BI dashboard reads cached results with low latency, refreshed on a schedule and incrementally when possible] O3{Object: managed table / view / materialized view} end subgraph Req4[Requirement 4] R4[Provide a session-scoped projection inside a single notebook that disappears when the notebook detaches] O4{Object: temporary view / external table / materialized view} end ```