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Updated Free Databricks Databricks-Certified-Data-Analyst-Associate Test Engine Questions with 118 Q&As

The Best Data Analyst Databricks-Certified-Data-Analyst-Associate Professional Exam Questions

Databricks Databricks-Certified-Data-Analyst-Associate Exam Syllabus Topics:

Topic Details
Topic 1
  • 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.
Topic 2
  • 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.
Topic 3
  • 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.
Topic 4
  • 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.
Topic 5
  • 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.

 

NO.34 A data analyst created and is the owner of the managed table my_ table. They now want to change ownership of the table to a single other user using Data Explorer.
Which of the following approaches can the analyst use to complete the task?

 
 
 
 
 

NO.35 A data analyst wants to create a Databricks SQL dashboard with multiple data visualizations and multiple counters. What must be completed before adding the data visualizations and counters to the dashboard?

 
 
 
 

NO.36 A data analyst has been asked to produce a visualization that shows the flow of users through a website.
Which of the following is used for visualizing this type of flow?

 
 
 
 
 

NO.37 A data engineer wants to schedule their Databricks SQL dashboard to refresh once per day, but they only want the associated SQL endpoint to be running when it is necessary.
Which of the following approaches can the data engineer use to minimize the total running time of the SQL endpoint used in the refresh schedule of their dashboard?

 
 
 
 
 

NO.38 A data analyst has been asked to produce a visualization that shows the flow of users through a website.
Which of the following is used for visualizing this type of flow?

 
 
 
 
 

NO.39 What is a benefit of using Databricks SQL for business intelligence (Bl) analytics projects instead of using third-party Bl tools?

 
 
 
 

NO.40 Which of the following data workloads will utilize a Gold table as its source?

 
 
 
 
 

NO.41 A data analyst is processing a complex aggregation on a table with zero null values and the query returns the following result:

Which query did the analyst execute in order to get this result?

 
 
 
 

NO.42 What describes Partner Connect in Databricks?

 
 
 
 

NO.43 Data engineers and data analysts are working together on a data pipeline. The data engineer is working on the raw, bronze, and silver layers of the pipeline using Python, and the data analyst is working on the gold layer of the pipeline using SQL. The raw source of the pipeline is a streaming input. They now want to migrate their pipeline to use Delta Live Tables.
Which of the following changes will need to be made to the pipeline when migrating to Delta Live Tables?

 
 
 
 

NO.44 A data analyst has created a Delta table sales that is used by the entire data analysis team. They want help from the data engineering team to implement a series of tests to ensure the data is clean. However, the data engineering team uses Python for its tests rather than SQL.
Which command could the data engineering team use to access sales in PySpark?

 
 
 
 

NO.45 A stakeholder has provided a data analyst with a lookup dataset in the form of a 50-row CSV file. The data analyst needs to upload this dataset for use as a table in Databricks SQL.
Which approach should the data analyst use to quickly upload the file into a table for use in Databricks SOL?

 
 
 
 

NO.46 A data engineer is running code in a Databricks Repo that is cloned from a central Git repository. A colleague informs them that changes have been made and synced to the central Git repository. The data engineer now needs to sync their Databricks Repo to get the changes from the central Git repository.
Which of the following Git operations does the data engineer need to run to accomplish this task?

 
 
 
 
 

NO.47 A data analyst is working with the following table my_table:
customer_name dollars_spent
Hex Sprockets [125.34, 100.15, 9003.99]
Dented Fenders [16.99, 200.85, 33.49, 88.17]
The analyst wants to divide each value in the dollars_spent array by 100 to get the spend in terms of hundreds of dollars using the following code block:
SELECT
customer_name,
_______
FROM my_table;
Which line of code can be used to fill in the blank so that the above code block successfully completes the task?

 
 
 
 

NO.48 A data analyst has been asked to use the below table sales_table to rank products within region by the sales.
Input table:
region product sales
WEST A 1880.59
EAST A 2045.99
EAST B 4583.23
WEST B 3391.19
The result of the query should look like this:
region product rank
EAST B 1
EAST A 2
WEST B 1
WEST A 2
Which query will accomplish this task?

 
 
 
 
 
 
 
 

NO.49 Which location can be used to determine the owner of a managed table?

 
 
 
 

NO.50 Which of the following approaches can be used to ingest data directly from cloud-based object storage?

 
 
 
 
 

NO.51 A data analyst is troubleshooting a query in Databricks SQL that fails when processing large datasets and complex join operations. Logs indicate that the job consistently aborts due to resource constraint errors on the cluster.
Which Query Profile metric should the analyst use to identify the operator that is causing resource overuse?

 
 
 
 

NO.52 Which of the following layers of the medallion architecture is most commonly used by data analysts?

 
 
 
 
 

NO.53 Which open-source project helps to enable the data lakehouse by adding organization, reliability, performance, and data governance to data lake architectures?

 
 
 
 

NO.54 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?

 
 
 
 

NO.55 Which statement describes descriptive statistics?

 
 
 
 

NO.56 A data analyst has a series of queries in a SQL program. The data analyst wants this program to run every day. They only want the final query in the program to run on Sundays. They ask for help from the data engineering team to complete this task.
Which of the following approaches could be used by the data engineering team to complete this task?

 
 
 
 
 

NO.57 A data engineering team has created a Structured Streaming pipeline that processes data in micro-batches and populates gold-level tables. The microbatches are triggered every minute.
A data analyst has created a dashboard based on this gold-level data. The project stakeholders want to see the results in the dashboard updated within one minute or less of new data becoming available within the gold-level tables.
Which of the following cautions should the data analyst share prior to setting up the dashboard to complete this task?

 
 
 
 
 

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