What Is Databricks?: 10 practice questions

Question 1 of 10

Which description best captures Databricks?

1. AA dashboard-only product for visualizing reports from a dedicated data warehouse
2. BA cloud object store that replaces processing and governance
3. CA source-control service limited to data engineering code
4. DA unified, open analytics platform for data, analytics, and AI solutions

Question 2 of 10

What does a data lakehouse combine?

1. ABenefits of data lakes and data warehouses
2. BFeatures of dashboards and mobile apps
3. CFeatures of notebooks and source-control repositories
4. DFunctions of compute clusters and job schedulers

Question 3 of 10

What is the core purpose of data engineering in the platform?

1. AMake data available, clean, and useful for downstream work
2. BKeep source data isolated for each downstream workload
3. CLimit organizational data to machine-learning experiments
4. DReplace business decisions with automatically generated reports

Question 4 of 10

How does the Databricks platform relate to a customer's cloud environment?

1. AIt delegates analytics processing to dashboards in the customer's browser
2. BIt replaces cloud security with permissions stored in source-control folders
3. CIt integrates with cloud storage and security while managing cloud infrastructure
4. DIt disconnects cloud storage and moves every governed dataset into isolated notebook files

Question 5 of 10

Which organizational problem can a lakehouse help address?

1. AExcessive use of open formats across machine-learning projects
2. BA lack of separately duplicated data copies for each individual analytics team
3. CIsolated systems and redundant data for different analytical workloads
4. DOverreliance on a shared source of truth for reporting workloads

Question 6 of 10

Which languages does the product overview name for composing ETL logic?

1. APython, Swift, and Ruby
2. BSQL, JavaScript, and Kotlin
3. CSQL, Python, and Scala
4. DScala, PHP, and Go

Question 7 of 10

Which set consists entirely of use cases supported by the Databricks platform?

1. APayroll processing, mobile telephony, business intelligence, and web hosting
2. BData engineering, business intelligence, machine learning, and real-time analytics
3. CSource-code licensing, device repair, data engineering, and office printing
4. DEmail hosting, endpoint antivirus management, machine learning, and internet domain registration

Question 8 of 10

A company has separate systems for BI and machine learning, duplicated datasets, and inconsistent refreshes. It wants standard-format data and a shared foundation for both workloads. Which platform idea best fits?

1. AAdopt a lakehouse to combine lake and warehouse benefits on shared data
2. BCreate another warehouse dedicated to machine learning and copy data nightly
3. CStore team data in separate notebooks and reconcile it manually
4. DReplace analytical storage with dashboards that retain their own source extracts

Question 9 of 10

Engineers, analysts, and data scientists need consistent data, but each group also needs a different workload. The organization wants less synchronization overhead. Which approach matches the platform overview?

1. ARestrict the platform to engineering and export files for every other role
2. BGive every role an isolated database and synchronize copies after each project
3. CLet the roles use one lakehouse as their shared source of truth
4. DUse one dashboard for storage and separate downloads

Question 10 of 10

A team must build ETL in SQL or Python, schedule the work, and serve the same governed data to BI and AI consumers. Which interpretation of Databricks is most accurate?

1. AIt is a SQL editor that exports to separate AI tools
2. BIt is a unified platform spanning engineering, orchestration, analytics, and AI
3. CIt is a cloud file browser that delegates transformation and governance to dashboards
4. DIt is an AI model host that requires external products for ingestion and analytics