Databricks-DA-Assoc Understanding the Databricks Platform — All Questions With Answers

Question 1

A data analyst needs to share a dashboard with stakeholders who do not have access to the underlying Databricks workspace. Which feature should the analyst use to enable this access?

Accepted Answer

Configure the dashboard for 'Share with public' or specific external guest access.. Databricks Dashboards (formerly Lakeview) allow analysts to share dashboards with any user or group in the Databricks account, even if they do not have access to the specific workspace where the dashboard was created. This requires the workspace to be enabled for identity federation. This feature provides a secure, read-only experience for stakeholders without requiring them to be workspace members.

Answer

Export the dashboard as a PDF and email it directly.

Answer

Provide credentials to a service account.

Answer

Grant full workspace access to the stakeholders.

Question 2

Refer to the exhibit. What is the purpose of using the Databricks CLI command shown?

Accepted Answer

To list the contents of a specific folder in the workspace.. The Databricks Certified Data Analyst Associate exam focuses on Databricks SQL, data visualization, and workspace navigation via the UI. CLI operations are part of the Data Engineer or Platform Administrator tracks. Furthermore, the question refers to an exhibit that is not provided, making it impossible to verify the specific command or the correctness of the answer.

Answer

To install a new library on the cluster.

Answer

To trigger an automated job execution.

Answer

To view the logs of a failed cluster.

Question 3

A data analyst is building a dashboard in Databricks SQL and wants the underlying query results to refresh automatically every 15 minutes so stakeholders see near-real-time sales figures. The source is a Delta table that is updated by a streaming job throughout the day. Which Databricks SQL feature should the analyst configure?

Accepted Answer

A scheduled query with a refresh schedule on the dashboard. Databricks SQL dashboards can be refreshed by scheduled queries that run on a cadence and update the dashboard's datasets. A 15-minute schedule aligns with the near-real-time requirement and works against a Delta table that is continuously updated, without requiring manual refreshes or additional pipeline infrastructure.

Answer

Query caching on the SQL warehouse

Answer

A materialized view with automatic refresh

Answer

Delta Live Tables with a continuous pipeline

Question 4

A data analyst has been using a shared all-purpose cluster to explore data but now must schedule a recurring dashboard refresh that runs every morning at 6:00 AM without manual intervention. The cluster is currently started manually each day. Which Databricks compute resource should the analyst use instead for the scheduled workload?

Accepted Answer

A Databricks SQL Warehouse configured with a schedule and auto-stop enabled. A Databricks SQL Warehouse is the correct compute for scheduled SQL analytics and dashboard refreshes. It supports scheduled start/stop, auto-stop, and scaling, so the 6:00 AM refresh runs without a person starting a cluster. All-purpose and personal compute are interactive resources, and a job cluster is for job execution rather than serving dashboard queries.

Answer

The existing all-purpose cluster with a cron schedule added to the notebook

Answer

A job cluster created automatically for each scheduled notebook run

Answer

A personal compute resource assigned only to the analyst's user account

Question 5

A data analyst is preparing to query a large sales Delta table from Databricks SQL. The analyst wants to reduce the volume of data scanned and lower query cost. Which TWO Databricks platform capabilities should the analyst rely on? (Choose two.)

Accepted Answer

Delta Lake data skipping using column statistics and file-level min/max metadata. Delta Lake data skipping prunes files using stored min/max statistics so fewer files are read, and Photon vectorizes execution to process the remaining data faster. Together they reduce bytes scanned and warehouse-seconds consumed when querying the large sales Delta table, directly lowering cost. The other choices affect idle billing, parallelism, or observability rather than scan volume.

Answer

Increasing the number of worker nodes on the SQL warehouse

Answer

Setting the SQL warehouse to auto-stop after a long idle period

Answer

Enabling verbose query history logging for the warehouse

Question 6

A data analyst is new to a Databricks workspace and needs to run an ad-hoc SQL query on a table stored in Unity Catalog. The analyst wants to ensure that the query runs on a cluster configured with the appropriate runtime and libraries, and that the cluster is automatically terminated after a period of inactivity to save costs. Which cluster type should the analyst use?

Accepted Answer

All-purpose cluster. All-purpose clusters are the correct choice for interactive ad-hoc SQL queries because they allow custom runtime and library configurations and support auto-termination after inactivity. SQL warehouses are for SQL-only workloads without custom libraries, job clusters are for automated jobs, and instance pools are a supporting resource, not a cluster type for running queries.

Answer

SQL warehouse

Answer

Job cluster

Answer

Instance pool

Question 7

A data analyst is working in a Databricks workspace and needs to ensure that their notebook code is version-controlled and collaborative. Which TWO actions should they take?

Accepted Answer

Use the built-in Databricks Repos feature to connect to a Git provider.. Integrating version control and collaboration is essential for professional data engineering workflows. By linking notebooks to Git providers, analysts ensure that changes are tracked, auditable, and easily revertible. This standard practice prevents accidental data loss and fosters teamwork, allowing multiple contributors to manage code repositories effectively within the Databricks environment while maintaining a single source of truth for all analytical project documentation and complex transformation logic.

Answer

Copy and paste code into a local text file.

Answer

Create a new notebook file for every code change.

Answer

Download the notebook to their local machine every hour.

Question 8

Refer to the exhibit. Given the provided JSON configuration for a Databricks cluster, what is the primary use case for this resource?

Accepted Answer

Interactive data analysis and notebook development.. Refer to the exhibit. The configuration shows an all-purpose cluster with autoscaling enabled. All-purpose clusters are primarily used for interactive development and data exploration within notebooks. Because they consume more DBU resources compared to job clusters, setting an idle termination limit is a cost-optimization best practice. Understanding cluster types is fundamental for managing platform costs and ensuring that resources are allocated appropriately based on the specific requirements of the workload being executed.

Answer

Running automated production ETL jobs.

Answer

Long-running streaming data ingestion.

Answer

Batch processing of large ML models.

Question 9

Which component of the Databricks Data Intelligence Platform allows users to discover, govern, and share data across the entire organization?

Accepted Answer

Unity Catalog. Unity Catalog is the centralized governance solution for data, analytics, and AI on the Databricks platform. It provides a single interface to manage permissions, track data lineage, and discover assets. Mastery of Unity Catalog is essential for any data analyst as it ensures that data access is secure, compliant, and transparent, effectively bridging the gap between raw storage and meaningful, governed business insights for all users.

Answer

Databricks SQL

Answer

Delta Live Tables

Answer

Compute Clusters

Question 10

Which THREE of the following are benefits of using Delta Lake over standard Parquet files in Databricks?

Accepted Answer

ACID transaction support. Delta Lake introduces ACID transactions, time travel, and schema enforcement to the data lake, transforming it into a lakehouse. These features are critical for maintaining data integrity in complex production environments. Understanding these benefits allows analysts to make informed decisions about storage formats, ensuring that the data platform remains reliable, scalable, and capable of handling complex analytical requirements without risking data corruption or inconsistency.

Answer

Automatic data compression to non-standard formats

Answer

The ability to run queries without a compute engine

Question 11

A data analyst is troubleshooting a performance issue in a notebook. The query runs slowly when processing a large table. Which approach should the analyst take to improve performance?

Accepted Answer

Run the 'OPTIMIZE' command on the Delta table.. Performance tuning in Databricks often involves examining how data is stored and accessed. Identifying bottlenecks like small files or lack of partitioning is key. By using built-in optimization commands, analysts can improve query speed significantly. This process is a core skill for any Databricks analyst, as it directly impacts the cost of compute resources and the user experience when working with massive, real-world datasets.

Answer

Increase the number of users connected to the workspace.

Answer

Delete the table and re-create it without Delta Lake.

Answer

Force the notebook to run on a single-node cluster.

Question 12

Refer to the exhibit. What is the most appropriate action to resolve this access issue?

Accepted Answer

Request the workspace administrator to grant appropriate privileges in Unity Catalog.. Refer to the exhibit. This error indicates a failure in the Unity Catalog permission model. When a user lacks the necessary 'USE' or 'SELECT' grants on a catalog, they are blocked from accessing any data within it. Understanding how Unity Catalog manages access at the catalog, schema, and table levels is vital for analysts to troubleshoot access issues and comply with organizational security policies.

Answer

Change the cluster configuration to use a different Spark version.

Answer

Move the data to a local file in DBFS.

Answer

Re-create the table in a different schema.

Question 13

A data analyst needs to ensure that sensitive information in a table is not visible to unauthorized users. Which Unity Catalog feature is the most efficient way to achieve this at the row level?

Accepted Answer

Apply Row Filters and Column Masks in Unity Catalog.. Row-level security (RLS) and column-level security are fundamental features of Unity Catalog that enable fine-grained access control. By applying these policies, organizations can ensure compliance with privacy regulations while maintaining data usability. Understanding how to define these filters allows analysts to secure data effectively without creating multiple copies of the same dataset for different user groups, which simplifies maintenance and ensures consistency.

Answer

Create a separate view for each user group.

Answer

Use hard-coded SQL 'WHERE' clauses in every notebook.

Answer

Move sensitive data to a completely separate, private workspace.

Question 14

What is the primary function of the 'Databricks Assistant' within the notebook environment?

Accepted Answer

To assist in writing, debugging, and explaining notebook code.. The Databricks Assistant is an AI-powered coding companion designed to help users write, debug, and optimize code faster. By leveraging context-aware suggestions, it helps analysts become more efficient. Understanding how to use the Assistant is beneficial for streamlining development workflows, as it assists with complex syntax, troubleshooting common errors, and generating boilerplate code, allowing the analyst to focus on the core logic of their data analysis tasks.

Answer

To automatically execute all notebooks in a production pipeline.

Answer

To manage user permissions across the entire workspace.

Answer

To store and back up notebook versions automatically.

Question 15

Which TWO of the following are true regarding Databricks SQL Warehouses?

Accepted Answer

They are specifically optimized for SQL-based analytical queries.. SQL Warehouses are specialized compute resources optimized for SQL workloads. Understanding the difference between these and general-purpose clusters is crucial for analysts, as warehouses offer features like serverless startup and auto-stop, which significantly optimize cost and performance. These warehouses enable the platform's BI and dashboarding capabilities, making them a cornerstone of the data analyst's toolkit for delivering consistent, reliable reports to business stakeholders.

Answer

They must be manually started every time a user runs a query.

Answer

They support the same multi-language notebook features as all-purpose clusters.

Answer

They are only available for administrative users.

Question 16

An analyst needs to combine data from a Delta table in the 'dev' catalog with a CSV file uploaded to a volume. Which feature allows the analyst to manage both in a single query?

Accepted Answer

Unity Catalog Volumes. Unity Catalog Volumes enable analysts to manage non-tabular data, such as CSV or JSON files, alongside traditional Delta tables. This unification simplifies the data integration process. By treating files in volumes as first-class objects within the catalog, analysts can use SQL to query and join disparate data sources, reducing the complexity of data pipelines and making it easier to perform multi-source analyses within a secure, governed environment.

Answer

External locations

Answer

Databricks File System (DBFS) mounting

Answer

Manual file upload via a web browser

Question 17

Which Databricks feature provides a detailed, lineage-based view of how data flows from source to destination?

Accepted Answer

Unity Catalog Data Lineage. Data lineage in Unity Catalog tracks the relationships between data assets, transformations, and end-users. This visibility is essential for impact analysis, debugging, and compliance. Understanding lineage helps analysts understand the origin of their data and the downstream effects of any changes they make, ensuring that business stakeholders always have confidence in the data's quality, provenance, and the transformation logic applied throughout the analytical pipeline.

Answer

Databricks SQL Audit Logs

Answer

Delta Live Tables Pipeline Monitoring

Answer

Cluster Event Logs

Question 18

A data analyst needs to perform ad-hoc SQL queries on a large dataset while ensuring the compute resources automatically terminate when idle to minimize costs. Which compute resource is most appropriate for this task?

Accepted Answer

SQL Warehouse. SQL Warehouses are designed specifically for SQL-based workloads, supporting BI tools and ad-hoc analysis through the SQL editor. They feature auto-stop functionality, which shuts down the cluster after a specified period of inactivity, directly addressing the cost-optimization requirement. Understanding the distinction between SQL Warehouses and All-Purpose clusters is vital for analysts, as Warehouses provide optimized performance for SQL queries and efficient resource management for collaborative reporting environments.

Answer

Job Compute

Answer

All-Purpose Compute

Answer

Delta Live Tables Pipeline

Question 19

Which TWO of the following statements accurately describe the relationship between Databricks SQL Warehouses and Delta Lake?

Accepted Answer

SQL Warehouses utilize Delta Lake's transaction log to ensure consistent query results.. Databricks SQL Warehouses provide the compute layer to execute ANSI-compliant SQL against data stored in Delta Lake format. Delta Lake serves as the underlying storage layer, providing ACID transactions and schema enforcement. Analysts must understand this separation, as it allows compute resources to scale independently from storage. This architecture ensures that SQL Warehouses can efficiently query massive volumes of data while leveraging the reliability and performance optimizations inherent in the Delta Lake storage structure.

Answer

SQL Warehouses must always be co-located in the same cloud region as the Delta Lake storage.

Answer

Delta Lake is a compute engine that replaces the need for SQL Warehouses.

Answer

SQL Warehouses require all data to be imported into a proprietary internal database format.

Question 20

Refer to the exhibit. A data analyst attempts to run a query in the SQL editor but receives the error displayed. Which action should the administrator take to resolve this?

Accepted Answer

Grant the user the 'CAN_USE' permission on the specific SQL Warehouse.. The error indicates a lack of the necessary access control privilege for the specific SQL Warehouse. In Databricks, permissions are managed via Access Control Lists (ACLs). The analyst requires the 'CAN_USE' permission to attach to and execute queries on a warehouse. Administrators must update the warehouse's permission settings in the Databricks workspace to grant this access level to the user or their associated group.

Answer

Restart the SQL Warehouse to refresh the user's session token.

Answer

Upgrade the user's workspace role to 'Workspace Admin'.

Answer

Increase the maximum number of clusters in the SQL Warehouse configuration.

Databricks-DA-Assoc Understanding the Databricks Platform — All Questions With Answers

A data analyst needs to share a dashboard with stakeholders who do not have access to the underlying Databricks workspace. Which feature should the analyst use to enable this access?

Refer to the exhibit. What is the purpose of using the Databricks CLI command shown?

Exhibit

A data analyst is preparing to query a large sales Delta table from Databricks SQL. The analyst wants to reduce the volume of data scanned and lower query cost. Which TWO Databricks platform capabilities should the analyst rely on? (Choose two.)

A data analyst is working in a Databricks workspace and needs to ensure that their notebook code is version-controlled and collaborative. Which TWO actions should they take?

Refer to the exhibit. Given the provided JSON configuration for a Databricks cluster, what is the primary use case for this resource?

Exhibit

Which component of the Databricks Data Intelligence Platform allows users to discover, govern, and share data across the entire organization?

Which THREE of the following are benefits of using Delta Lake over standard Parquet files in Databricks?

A data analyst is troubleshooting a performance issue in a notebook. The query runs slowly when processing a large table. Which approach should the analyst take to improve performance?

Refer to the exhibit. What is the most appropriate action to resolve this access issue?

Exhibit

A data analyst needs to ensure that sensitive information in a table is not visible to unauthorized users. Which Unity Catalog feature is the most efficient way to achieve this at the row level?

What is the primary function of the 'Databricks Assistant' within the notebook environment?

Which TWO of the following are true regarding Databricks SQL Warehouses?

An analyst needs to combine data from a Delta table in the 'dev' catalog with a CSV file uploaded to a volume. Which feature allows the analyst to manage both in a single query?

Which Databricks feature provides a detailed, lineage-based view of how data flows from source to destination?

A data analyst needs to perform ad-hoc SQL queries on a large dataset while ensuring the compute resources automatically terminate when idle to minimize costs. Which compute resource is most appropriate for this task?

Which TWO of the following statements accurately describe the relationship between Databricks SQL Warehouses and Delta Lake?

Refer to the exhibit. A data analyst attempts to run a query in the SQL editor but receives the error displayed. Which action should the administrator take to resolve this?

Exhibit

What is the primary purpose of the Databricks Catalog Explorer?

Which THREE features are provided by Unity Catalog to enhance data governance?

Which Databricks component is the primary interface for collaborative, interactive data analysis and visualization?

A data analyst is working in a notebook and notices that the query results are inconsistent compared to an earlier run, despite no code changes. What is the most likely cause?

Refer to the exhibit. An analyst receives this error when attempting to query a table. Which step should they take to fix this?

Exhibit

When sharing an analysis with stakeholders, what is the best practice for ensuring they can view the results without needing access to the underlying raw data?

A data analyst needs to share a notebook with a colleague who should be able to run the code but not modify it. Which permission level should the analyst grant to the colleague?

A Databricks workspace administrator wants to optimize costs and manage resources effectively. Which TWO of the following capabilities allow for automatic cluster termination and scaling?

Which component of the Databricks platform acts as the central entry point for users to manage their data, notebooks, and experiments?

Refer to the exhibit. An analyst is reviewing a cluster configuration JSON. If the cluster is currently idle, what happens after 40 minutes of inactivity?

Exhibit

An analyst opens the Databricks SQL editor and wants to browse the tables available in the workspace's Unity Catalog metastore before writing a query. Which workspace object should the analyst use to navigate catalogs, schemas, and tables?

A data analyst needs to run a scheduled SQL query every morning and deliver the result to a finance team as a CSV file in cloud storage. The query logic is already tested in a Databricks SQL query. Which Databricks capability should the analyst use to automate this delivery?

A data analyst is new to a Databricks workspace and needs to understand which compute options are available for running SQL and notebooks. Which TWO of the following statements accurately describe Databricks compute in this context? (Choose two.)

A data analyst has a notebook that reads a Delta table and produces summary statistics. The analyst wants colleagues to see the latest results in a dashboard without rerunning the notebook manually each time. Which Databricks capability should the analyst use to keep the dashboard current?

A data analyst is new to a Databricks workspace and needs to work with data stored in Unity Catalog. The analyst wants to understand which statements about Unity Catalog are accurate. (Choose two.)

An analyst wants to include a chart from a Databricks SQL query in a presentation and also allow stakeholders to explore the same query interactively later. Which two-part approach best fits this need?

A data analyst is building a dashboard in Databricks SQL and needs to give viewers the ability to change the date range and a region filter without editing the underlying query. The dashboard should refresh results based on the viewer's selections. Which feature should the analyst use?

A data analyst is preparing to publish a Databricks SQL dashboard for a team of business users. The analyst wants the dashboard to load quickly and to remain usable as the underlying Delta table grows. Which two practices should the analyst follow? (Choose two.)

Databricks-DA-Assoc Understanding the Databricks Platform — All Questions With Answers

A data analyst needs to share a dashboard with stakeholders who do not have access to the underlying Databricks workspace. Which feature should the analyst use to enable this access?

Refer to the exhibit. What is the purpose of using the Databricks CLI command shown?

Exhibit

A data analyst is preparing to query a large sales Delta table from Databricks SQL. The analyst wants to reduce the volume of data scanned and lower query cost. Which TWO Databricks platform capabilities should the analyst rely on? (Choose two.)

A data analyst is working in a Databricks workspace and needs to ensure that their notebook code is version-controlled and collaborative. Which TWO actions should they take?

Refer to the exhibit. Given the provided JSON configuration for a Databricks cluster, what is the primary use case for this resource?

Exhibit

Which component of the Databricks Data Intelligence Platform allows users to discover, govern, and share data across the entire organization?

Which THREE of the following are benefits of using Delta Lake over standard Parquet files in Databricks?

A data analyst is troubleshooting a performance issue in a notebook. The query runs slowly when processing a large table. Which approach should the analyst take to improve performance?

Refer to the exhibit. What is the most appropriate action to resolve this access issue?

Exhibit

A data analyst needs to ensure that sensitive information in a table is not visible to unauthorized users. Which Unity Catalog feature is the most efficient way to achieve this at the row level?

What is the primary function of the 'Databricks Assistant' within the notebook environment?

Which TWO of the following are true regarding Databricks SQL Warehouses?

An analyst needs to combine data from a Delta table in the 'dev' catalog with a CSV file uploaded to a volume. Which feature allows the analyst to manage both in a single query?

Which Databricks feature provides a detailed, lineage-based view of how data flows from source to destination?

A data analyst needs to perform ad-hoc SQL queries on a large dataset while ensuring the compute resources automatically terminate when idle to minimize costs. Which compute resource is most appropriate for this task?

Which TWO of the following statements accurately describe the relationship between Databricks SQL Warehouses and Delta Lake?

Refer to the exhibit. A data analyst attempts to run a query in the SQL editor but receives the error displayed. Which action should the administrator take to resolve this?

Exhibit

What is the primary purpose of the Databricks Catalog Explorer?

Which THREE features are provided by Unity Catalog to enhance data governance?

Which Databricks component is the primary interface for collaborative, interactive data analysis and visualization?

A data analyst is working in a notebook and notices that the query results are inconsistent compared to an earlier run, despite no code changes. What is the most likely cause?

Refer to the exhibit. An analyst receives this error when attempting to query a table. Which step should they take to fix this?

Exhibit

When sharing an analysis with stakeholders, what is the best practice for ensuring they can view the results without needing access to the underlying raw data?

A data analyst needs to share a notebook with a colleague who should be able to run the code but not modify it. Which permission level should the analyst grant to the colleague?

A Databricks workspace administrator wants to optimize costs and manage resources effectively. Which TWO of the following capabilities allow for automatic cluster termination and scaling?

Which component of the Databricks platform acts as the central entry point for users to manage their data, notebooks, and experiments?

Refer to the exhibit. An analyst is reviewing a cluster configuration JSON. If the cluster is currently idle, what happens after 40 minutes of inactivity?

Exhibit

An analyst opens the Databricks SQL editor and wants to browse the tables available in the workspace's Unity Catalog metastore before writing a query. Which workspace object should the analyst use to navigate catalogs, schemas, and tables?

A data analyst needs to run a scheduled SQL query every morning and deliver the result to a finance team as a CSV file in cloud storage. The query logic is already tested in a Databricks SQL query. Which Databricks capability should the analyst use to automate this delivery?

A data analyst is new to a Databricks workspace and needs to understand which compute options are available for running SQL and notebooks. Which TWO of the following statements accurately describe Databricks compute in this context? (Choose two.)

A data analyst has a notebook that reads a Delta table and produces summary statistics. The analyst wants colleagues to see the latest results in a dashboard without rerunning the notebook manually each time. Which Databricks capability should the analyst use to keep the dashboard current?