Databricks Databricks-Certified-Data-Analyst-Associate 問題集

試験コード：Databricks-Certified-Data-Analyst-Associate

試験名称：Databricks Certified Data Analyst Associate Exam

最近更新時間：2026-07-07

問題と解答：全118問

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質問 1：
Which of the following describes how Databricks SQL should be used in relation to other business intelligence (BI) tools like Tableau, Power BI, and looker?
A. As an exact substitute with the same level of functionality
B. As a substitute with less functionality
C. As a complementary tool for quick in-platform Bl work
D. As a complete replacement with additional functionality
E. As a complementary tool for professional-grade presentations
正解：C
解説: (Topexam メンバーにのみ表示されます)

質問 2：
A data analyst has created a Query in Databricks SQL, and now they want to create two data visualizations from that Query and add both of those data visualizations to the same Databricks SQL Dashboard.
Which of the following steps will they need to take when creating and adding both data visualizations to the Databricks SQL Dashboard?
A. They will need to add two separate visualizations to the dashboard based on the same Query.
B. They will need to copy the Query and create one data visualization per query.
C. They will need to create two separate dashboards.
D. They will need to decide on a single data visualization to add to the dashboard.
E. They will need to alter the Query to return two separate sets of results.
正解：A
解説: (Topexam メンバーにのみ表示されます)

質問 3：
Which of the following is a benefit of Databricks SQL using ANSI SQL as its standard SQL dialect?
A. It allows for the use of Photon ' s computation optimizations
B. It is easy to migrate existing SQL queries to Databricks SQL
C. It has increased customization capabilities
D. It is more compatible with Spark ' s interpreters
E. It is more performant than other SQL dialects
正解：B
解説: (Topexam メンバーにのみ表示されます)

質問 4：
A data analyst needs to share a Databricks SQL dashboard with stakeholders that are not permitted to have accounts in the Databricks deployment. The stakeholders need to be notified every time the dashboard is refreshed.
Which approach can the data analyst use to accomplish this task with minimal effort/
A. By downloading the dashboard as a PDF and emailing it to the stakeholders each time it is refreshed
B. By granting the stakeholders ' email addresses to the SQL Warehouse (formerly known as endpoint) subscribers list
C. By adding the stakeholders ' email addresses to the refresh schedule subscribers list
D. By granting the stakeholders ' email addresses permissions to the dashboard
正解：C
解説: (Topexam メンバーにのみ表示されます)

質問 5：
A data analyst has two data sources that are providing similar but complementary information. The analyst wants to combine these sources of data into a single, comprehensive dataset for ongoing use for their team in a variety of different projects.
Which term is used to describe this type of work?
A. Data testing
B. Data blending
C. Last-mile ETL
D. Ad-hoc improvements
正解：B
解説: (Topexam メンバーにのみ表示されます)

質問 6：
A data engineer wants to create a relational object by pulling data from two tables. The relational object does not need to be used by other data engineers in other sessions. In order to save on storage costs, the data engineer wants to avoid copying and storing physical data.
Which of the following relational objects should the data engineer create?
A. Delta Table
B. Temporary view
C. Spark SQL Table
D. Database
E. View
正解：B
解説: (Topexam メンバーにのみ表示されます)

質問 7：
A data analyst wants to create a dashboard with three main sections: Development, Testing, and Production.
They want all three sections on the same dashboard, but they want to clearly designate the sections using text on the dashboard.
Which of the following tools can the data analyst use to designate the Development, Testing, and Production sections using text?
A. Separate color palettes for each section
B. Separate queries for each section
C. Separate endpoints for each section
D. Direct text written into the dashboard in editing mode
E. Markdown-based text boxes
正解：E
解説: (Topexam メンバーにのみ表示されます)

質問 8：
Where in the Databricks SQL workspace can a data analyst configure a refresh schedule for a query when the query is not attached to a dashboard or alert?
A. The Visualization editor
B. Data bxplorer
C. The Dashboard Editor
D. The Query Editor
正解：D
解説: (Topexam メンバーにのみ表示されます)

質問 9：
A BI analyst is building an analytical data model in Databricks using Delta Lake tables. The source system contains transactional sales data that changes frequently. The analyst chooses to apply the Data Vault 2.0 methodology to manage historical changes while ensuring scalability and auditability across multiple business domains.
Which component is used to capture the many-to-many relationship between hubs in a Data Vault v2 model?
A. Link Table
B. Reference Table
C. Hub Table
D. Satellite Table
正解：A
解説: (Topexam メンバーにのみ表示されます)

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Databricks Databricks-Certified-Data-Analyst-Associate 認定試験の出題範囲：

トピック	出題範囲
トピック 1	Databricks SQL: This topic discusses key and side audiences, users, Databricks SQL benefits, complementing a basic Databricks SQL query, schema browser, Databricks SQL dashboards, and the purpose of Databricks SQL endpoints warehouses. Furthermore, the delves into Serverless Databricks SQL endpoint warehouses, trade-off between cluster size and cost for Databricks SQL endpoints warehouses, and Partner Connect. Lastly it discusses small-file upload, connecting Databricks SQL to visualization tools, the medallion architecture, the gold layer, and the benefits of working with streaming data.
トピック 2	Data Visualization and Dashboarding: Sub-topics of this topic are about of describing how notifications are sent, how to configure and troubleshoot a basic alert, how to configure a refresh schedule, the pros and cons of sharing dashboards, how query parameters change the output, and how to change the colors of all of the visualizations. It also discusses customized data visualizations, visualization formatting, Query Based Dropdown List, and the method for sharing a dashboard.
トピック 3	SQL in the Lakehouse: It identifies a query that retrieves data from the database, the output of a SELECT query, a benefit of having ANSI SQL, access, and clean silver-level data. It also compares and contrasts MERGE INTO, INSERT TABLE, and COPY INTO. Lastly, this topic focuses on creating and applying UDFs in common scaling scenarios.
トピック 4	Data Management: The topic describes Delta Lake as a tool for managing data files, Delta Lake manages table metadata, benefits of Delta Lake within the Lakehouse, tables on Databricks, a table owner’s responsibilities, and the persistence of data. It also identifies management of a table, usage of Data Explorer by a table owner, and organization-specific considerations of PII data. Lastly, the topic it explains how the LOCATION keyword changes, usage of Data Explorer to secure data.
トピック 5	Analytics applications: It describes key moments of statistical distributions, data enhancement, and the blending of data between two source applications. Moroever, the topic also explains last-mile ETL, a scenario in which data blending would be beneficial, key statistical measures, descriptive statistics, and discrete and continuous statistics.

参照：https://www.databricks.com/learn/certification/data-analyst-associate

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