Set up and configure an Azure Databricks environment

DP-750 · 35 questions

• A city open-data team runs nightly batch transforms for 311 tickets and needs compute that starts for the job and shuts down when the run finishes. Which compute should they select?
• County public-health analysts need interactive SQL dashboards over clinic case metrics without managing classic Spark clusters. Which Azure Databricks compute should they use?
• Transit operations wants ad-hoc notebook exploration of ridership without leaving idle clusters burning budget overnight. Which compute choice best fits?
• Housing authority data engineers need a workspace cluster that several developers can attach to while collaboratively building lease-enrichment notebooks. Which compute pattern should they choose?
• Emergency management weather-alert joins spill memory during peak storms. What compute change should the data engineer make first?
• The permits office schedules weekend PDF-extract backfills that vary sharply in volume. How should they configure compute scaling?
• Library analytics leaves all-purpose clusters running after analysts disconnect, driving idle charges. Which setting should they apply?
• A water utility runs recurring IoT ingest jobs and wants shorter cold-start time for sensor backfills. Which compute feature should they use?
• City finance runs warehouse SQL that aggregates high-volume parking citation facts and needs faster query execution. Which feature should they enable?
• County IT must keep fraud-flag feature-prep notebooks reproducible across deploys. What should they pin on the compute configuration?
• A public-health notebook trains a simple clinic no-show model alongside ETL feature prep. Which runtime should the team select?
• The 311 pipeline must standardize addresses in-process on the job cluster. What should the data engineer do?
• Courts clerk leadership must limit who can attach to a cluster that processes sensitive case-index data. What should they configure?
• Parks department BI authors only write SQL against park visitation Delta tables. Which compute should the data engineer prefer?
• School-district attendance ETL must burst during enrollment week without unbounded spend. How should worker counts be set?
• Municipal architecture standards require different node traits for permit OCR enrichment versus wide resident-service joins. What selection principle should engineers follow?
• Open-data stewards need a connector library available to every notebook on a shared civic cluster without copying jars into each notebook. What should they do?
• County security asks who should be allowed to restart a production job cluster that processes resident PII extracts. What is the appropriate approach?
• A city lakehouse must keep permit silver tables from colliding across stages. How should Unity Catalog objects be named?
• A regional transit consortium will share anonymized ridership aggregates with external partners. What Unity Catalog naming consideration matters most when creating the catalog?
• A housing authority needs one top-level Unity Catalog boundary to hold all resident-services schemas. What object should they create first?
• Public works wants water-main break events organized separately from wastewater under the utilities catalog. What should they create?
• The clerk of courts needs Unity Catalog storage for scanned PDF evidence packages that enrichment jobs will read as files. Which object should they create?
• The 311 team wants analysts to query curated ticket outcomes without seeing internal disposition codes stored on the base table. How should they expose the data?
• Transit BI needs dashboards that stay fast during rush reporting on hourly boardings. Which Unity Catalog object should they use for pre-aggregated metrics?
• A county finance team needs Azure Databricks analysts to query live tables in an existing SQL Server permitting database without copying every table into the lakehouse first. Which Unity Catalog approach should they implement?
• Open-data engineers need a durable Unity Catalog table for published park schedules that Databricks manages end to end. Which action should they take?
• Emergency management already stores historical storm CSVs in ADLS and wants Azure Databricks to query them without rewriting the files. Which Unity Catalog object should they create?
• A city wants resident analysts using AI/BI Genie to discover the correct 311 domain tables when they ask natural-language questions about ticket metrics. What should data engineers configure?
• A municipal architecture board wants gold citizen-service metrics fully lifecycle-managed by Azure Databricks under Unity Catalog. Which table choice should they standardize on?
• A water utility lands raw IoT sensor files in ADLS and later produces cleansed silver readings for analytics. How should they mix Unity Catalog table types across layers?
• A library system receives periodic MARC export file drops that notebooks must read before loading catalog Delta tables. Which Unity Catalog object should they create for the landing files?
• A permits team wants Unity Catalog to reflect medallion layers for permit data under one subject-area boundary. How should they organize objects?
• County IT wants engineers to experiment with Unity Catalog objects for civic pipelines without risking production tables. Which approach should they take?
• A health department must keep PHI schemas separable from public open-data schemas inside the same Unity Catalog metastore. What naming practice should they adopt?