[May-2024] Databricks-Certified-Data-Analyst-Associate Exam Questions and Valid Databricks-Certified-Data-Analyst-Associate Dumps PDF [Q13-Q29]

[May-2024] Databricks-Certified-Data-Analyst-Associate Exam Questions and Valid Databricks-Certified-Data-Analyst-Associate Dumps PDF

Databricks-Certified-Data-Analyst-Associate Brain Dump: A Study Guide with Tips & Tricks for passing Exam

NEW QUESTION # 13
A data analyst has recently joined a new team that uses Databricks SQL, but the analyst has never used Databricks before. The analyst wants to know where in Databricks SQL they can write and execute SQL queries.
On which of the following pages can the analyst write and execute SQL queries?

• A. Data page
• B. Queries page
• C. Dashboards page
• D. SQL Editor page
• E. Alerts page

Answer: D

Explanation:
The SQL Editor page is where the analyst can write and execute SQL queries in Databricks SQL. The SQL Editor page has a query pane where the analyst can type or paste SQL statements, and a results pane where the analyst can view the query results in a table or a chart. The analyst can also browse data objects, edit multiple queries, execute a single query or multiple queries, terminate a query, save a query, download a query result, and more from the SQL Editor page. Reference: Create a query in SQL editor

NEW QUESTION # 14
A data analyst has a managed table table_name in database database_name. They would now like to remove the table from the database and all of the data files associated with the table. The rest of the tables in the database must continue to exist.
Which of the following commands can the analyst use to complete the task without producing an error?

• A. DELETE TABLE table_name FROM database_name;
• B. DROP DATABASE database_name;
• C. DROP TABLE database_name.table_name;
• D. DELETE TABLE database_name.table_name;
• E. DROP TABLE table_name FROM database_name;

Answer: C

NEW QUESTION # 15
A data analyst has created a user-defined function using the following line of code:
CREATE FUNCTION price(spend DOUBLE, units DOUBLE)
RETURNS DOUBLE
RETURN spend / units;
Which of the following code blocks can be used to apply this function to the customer_spend and customer_units columns of the table customer_summary to create column customer_price?

• A. SELECT price(customer_spend, customer_units) AS customer_price FROM customer_summary
• B. SELECT price FROM customer_summary
• C. SELECT double(price(customer_spend, customer_units)) AS customer_price FROM customer_summary
• D. SELECT function(price(customer_spend, customer_units)) AS customer_price FROM customer_summary
• E. SELECT PRICE customer_spend, customer_units AS customer_price FROM customer_summary

Answer: A

Explanation:
A user-defined function (UDF) is a function defined by a user, allowing custom logic to be reused in the user environment1. To apply a UDF to a table, the syntax is SELECT udf_name(column_name) AS alias FROM table_name2. Therefore, option E is the correct way to use the UDF price to create a new column customer_price based on the existing columns customer_spend and customer_units from the table customer_summary. Reference:
What are user-defined functions (UDFs)?
User-defined scalar functions - SQL
V

NEW QUESTION # 16
A data analyst creates a Databricks SQL Query where the result set has the following schema:
region STRING
number_of_customer INT
When the analyst clicks on the "Add visualization" button on the SQL Editor page, which of the following types of visualizations will be selected by default?

• A. Line Chart
• B. Violin Chart
• C. There is no default. The user must choose a visualization type.
• D. IBar Chart
• E. Histogram

Answer: D

Explanation:
According to the Databricks SQL documentation, when a data analyst clicks on the "Add visualization" button on the SQL Editor page, the default visualization type is Bar Chart. This is because the result set has two columns: one of type STRING and one of type INT. The Bar Chart visualization automatically assigns the STRING column to the X-axis and the INT column to the Y-axis. The Bar Chart visualization is suitable for showing the distribution of a numeric variable across different categories. Reference: Visualization in Databricks SQL, Visualization types

NEW QUESTION # 17
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

Answer: C

Explanation:
Databricks SQL is not meant to replace or substitute other BI tools, but rather to complement them by providing a fast and easy way to query, explore, and visualize data on the lakehouse using the built-in SQL editor, visualizations, and dashboards. Databricks SQL also integrates seamlessly with popular BI tools like Tableau, Power BI, and Looker, allowing analysts to use their preferred tools to access data through Databricks clusters and SQL warehouses. Databricks SQL offers low-code and no-code experiences, as well as optimized connectors and serverless compute, to enhance the productivity and performance of BI workloads on the lakehouse. Reference: Databricks SQL, Connecting Applications and BI Tools to Databricks SQL, Databricks integrations overview, Databricks SQL: Delivering a Production SQL Development Experience on the Lakehouse

NEW QUESTION # 18
A data organization has a team of engineers developing data pipelines following the medallion architecture using Delta Live Tables. While the data analysis team working on a project is using gold-layer tables from these pipelines, they need to perform some additional processing of these tables prior to performing their analysis.
Which of the following terms is used to describe this type of work?

• A. Last-mile
• B. Data testing
• C. Data enhancement
• D. Data blending
• E. Last-mile ETL

Answer: E

Explanation:
Last-mile ETL is the term used to describe the additional processing of data that is done by data analysts or data scientists after the data has been ingested, transformed, and stored in the lakehouse by data engineers. Last-mile ETL typically involves tasks such as data cleansing, data enrichment, data aggregation, data filtering, or data sampling that are specific to the analysis or machine learning use case. Last-mile ETL can be done using Databricks SQL, Databricks notebooks, or Databricks Machine Learning. Reference: Databricks - Last-mile ETL, Databricks - Data Analysis with Databricks SQL

NEW QUESTION # 19
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 create two separate dashboards.
• B. They will need to alter the Query to return two separate sets of results.
• C. They will need to add two separate visualizations to the dashboard based on the same Query.
• D. They will need to decide on a single data visualization to add to the dashboard.
• E. They will need to copy the Query and create one data visualization per query.

Answer: C

Explanation:
A data analyst can create multiple visualizations from the same query in Databricks SQL by clicking the + button next to the Results tab and selecting Visualization. Each visualization can have a different type, name, and configuration. To add a visualization to a dashboard, the data analyst can click the vertical ellipsis button beneath the visualization, select + Add to Dashboard, and choose an existing or new dashboard. The data analyst can repeat this process for each visualization they want to add to the same dashboard. Reference: Visualization in Databricks SQL, Visualize queries and create a dashboard in Databricks SQL

NEW QUESTION # 20
Which of the following statements describes descriptive statistics?

• A. A branch of statistics that uses a variety of data analysis techniques to infer properties of an underlying distribution of probability.
• B. A branch of statistics that uses quantitative variables that must take on a finite or countably infinite set of values.
• C. A branch of statistics that uses summary statistics to quantitatively describe and summarize data.
• D. A branch of statistics that uses quantitative variables that must take on an uncountable set of values.
• E. A branch of statistics that uses summary statistics to categorically describe and summarize data.

Answer: C

Explanation:
Descriptive statistics is a branch of statistics that uses summary statistics, such as mean, median, mode, standard deviation, range, frequency, or correlation, to quantitatively describe and summarize data. Descriptive statistics can help data analysts understand the main features of a data set, such as its central tendency, variability, or distribution. Descriptive statistics can also help data analysts visualize data using charts, graphs, or tables. Descriptive statistics do not make any inferences or predictions about the data, unlike inferential statistics, which use data analysis techniques to infer properties of an underlying population or probability distribution from a sample of data. Reference: Databricks - Descriptive Statistics, Databricks - Data Analysis with Databricks SQL

NEW QUESTION # 21
A data analyst has been asked to provide a list of options on how to share a dashboard with a client. It is a security requirement that the client does not gain access to any other information, resources, or artifacts in the database.
Which of the following approaches cannot be used to share the dashboard and meet the security requirement?

• A. Download a PNG file of the visualizations in the dashboard and share them with the client.
• B. Take a screenshot of the dashboard and share it with the client.
• C. Set a refresh schedule for the dashboard and enter the client's email address in the "Subscribers" box.
• D. Generate a Personal Access Token that is good for 1 day and share it with the client.
• E. Download the Dashboard as a PDF and share it with the client.

Answer: D

Explanation:
The approach that cannot be used to share the dashboard and meet the security requirement is D. Generating a Personal Access Token that is good for 1 day and sharing it with the client. This approach would give the client access to the Databricks workspace using the token owner's identity and permissions, which could expose other information, resources, or artifacts in the database1. The other approaches can be used to share the dashboard and meet the security requirement because:
A) Downloading the Dashboard as a PDF and sharing it with the client would only provide a static snapshot of the dashboard without any interactive features or access to the underlying data2.
B) Setting a refresh schedule for the dashboard and entering the client's email address in the "Subscribers" box would send the client an email with the latest dashboard results as an attachment or a link to a secure web page3. The client would not be able to access the Databricks workspace or the dashboard itself.
C) Taking a screenshot of the dashboard and sharing it with the client would also only provide a static snapshot of the dashboard without any interactive features or access to the underlying data4.
E) Downloading a PNG file of the visualizations in the dashboard and sharing them with the client would also only provide a static snapshot of the visualizations without any interactive features or access to the underlying data5. Reference:
1: Personal access tokens
2: Download as PDF
3: Automatically refresh a dashboard
4: Take a screenshot
5: Download a PNG file

NEW QUESTION # 22
A data analyst runs the following command:
INSERT INTO stakeholders.suppliers TABLE stakeholders.new_suppliers;
What is the result of running this command?

• A. The command fails because it is written incorrectly.
• B. The suppliers table now contains both the data it had before the command was run and the data from the new suppliers table, and any duplicate data is deleted.
• C. The suppliers table now contains only the data from the new suppliers table.
• D. The suppliers table now contains both the data it had before the command was run and the data from the new suppliers table, including any duplicate data.
• E. The suppliers table now contains the data from the new suppliers table, and the new suppliers table now contains the data from the suppliers table.

Answer: A

Explanation:
The command INSERT INTO stakeholders.suppliers TABLE stakeholders.new_suppliers is not a valid syntax for inserting data into a table in Databricks SQL. According to the documentation12, the correct syntax for inserting data into a table is either:
INSERT { OVERWRITE | INTO } [ TABLE ] table_name [ PARTITION clause ] [ ( column_name [, ...] ) | BY NAME ] query INSERT INTO [ TABLE ] table_name REPLACE WHERE predicate query The command in the question is missing the OVERWRITE or INTO keyword, and the query part that specifies the source of the data to be inserted. The TABLE keyword is optional and can be omitted. The PARTITION clause and the column list are also optional and depend on the table schema and the data source. Therefore, the command in the question will fail with a syntax error.
Reference:
INSERT | Databricks on AWS
INSERT - Azure Databricks - Databricks SQL | Microsoft Learn

NEW QUESTION # 23
Which of the following approaches can be used to connect Databricks to Fivetran for data ingestion?

• A. Use Partner Connect's automated workflow to establish a SQL warehouse (formerly known as a SQL endpoint) for Fivetran to interact with
• B. Use Delta Live Tables to establish a cluster for Fivetran to interact with
• C. Use Workflows to establish a cluster for Fivetran to interact with
• D. Use Partner Connect's automated workflow to establish a cluster for Fivetran to interact with
• E. Use Workflows to establish a SQL warehouse (formerly known as a SQL endpoint) for Fivetran to interact with

Answer: D

Explanation:
Partner Connect is a feature that allows you to easily connect your Databricks workspace to Fivetran and other ingestion partners using an automated workflow. You can select a SQL warehouse or a cluster as the destination for your data replication, and the connection details are sent to Fivetran. You can then choose from over 200 data sources that Fivetran supports and start ingesting data into Delta Lake. Reference: Connect to Fivetran using Partner Connect, Use Databricks with Fivetran

NEW QUESTION # 24
Which of the following layers of the medallion architecture is most commonly used by data analysts?

• A. All of these layers are used equally by data analysts
• B. None of these layers are used by data analysts
• C. Gold
• D. Bronze
• E. Silver

Answer: C

Explanation:
The gold layer of the medallion architecture contains data that is highly refined and aggregated, and powers analytics, machine learning, and production applications. Data analysts typically use the gold layer to access data that has been transformed into knowledge, rather than just information. The gold layer represents the final stage of data quality and optimization in the lakehouse. Reference: What is the medallion lakehouse architecture?

NEW QUESTION # 25
Data professionals with varying titles use the Databricks SQL service as the primary touchpoint with the Databricks Lakehouse Platform. However, some users will use other services like Databricks Machine Learning or Databricks Data Science and Engineering.
Which of the following roles uses Databricks SQL as a secondary service while primarily using one of the other services?

• A. Data engineer
• B. Business intelligence analyst
• C. Business analyst
• D. Data analyst
• E. SQL analyst

Answer: A

Explanation:
Data engineers are primarily responsible for building, managing, and optimizing data pipelines and architectures. They use Databricks Data Science and Engineering service to perform tasks such as data ingestion, transformation, quality, and governance. Data engineers may use Databricks SQL as a secondary service to query, analyze, and visualize data from the lakehouse, but this is not their main focus. Reference: Databricks SQL overview, Databricks Data Science and Engineering overview, Data engineering with Databricks

NEW QUESTION # 26
Which of the following statements about a refresh schedule is incorrect?

• A. A query being refreshed on a schedule does not use a SQL Warehouse (formerly known as SQL Endpoint).
• B. You must have workspace administrator privileges to configure a refresh schedule
• C. Refresh schedules can be configured in the Query Editor.
• D. A query can be refreshed anywhere from 1 minute lo 2 weeks
• E. A refresh schedule is not the same as an alert.

Answer: A

Explanation:
Refresh schedules are used to rerun queries at specified intervals, and these queries typically require computational resources to execute. In the context of a cloud data service like Databricks, this would typically involve the use of a SQL Warehouse (or a SQL Endpoint, as they were formerly known) to provide the necessary computational resources. Therefore, the statement is incorrect because scheduled query refreshes would indeed use a SQL Warehouse/Endpoint to execute the query.

NEW QUESTION # 27
A data team has been given a series of projects by a consultant that need to be implemented in the Databricks Lakehouse Platform.
Which of the following projects should be completed in Databricks SQL?

• A. Automating complex notebook-based workflows with multiple tasks
• B. Segmenting customers into like groups using a clustering algorithm
• C. Testing the quality of data as it is imported from a source
• D. Tracking usage of feature variables for machine learning projects
• E. Combining two data sources into a single, comprehensive dataset

Answer: E

Explanation:
Databricks SQL is a service that allows users to query data in the lakehouse using SQL and create visualizations and dashboards1. One of the common use cases for Databricks SQL is to combine data from different sources and formats into a single, comprehensive dataset that can be used for further analysis or reporting2. For example, a data analyst can use Databricks SQL to join data from a CSV file and a Parquet file, or from a Delta table and a JDBC table, and create a new table or view that contains the combined data3. This can help simplify the data management and governance, as well as improve the data quality and consistency. Reference:
Databricks SQL overview
Databricks SQL use cases
Joining data sources

NEW QUESTION # 28
A data analyst has a managed table table_name in database database_name. They would now like to remove the table from the database and all of the data files associated with the table. The rest of the tables in the database must continue to exist.
Which of the following commands can the analyst use to complete the task without producing an error?

• A. DELETE TABLE table_name FROM database_name;
• B. DROP DATABASE database_name;
• C. DROP TABLE database_name.table_name;
• D. DELETE TABLE database_name.table_name;
• E. DROP TABLE table_name FROM database_name;

Answer: C

Explanation:
The DROP TABLE command removes a table from the metastore and deletes the associated data files. The syntax for this command is DROP TABLE [IF EXISTS] [database_name.]table_name;. The optional IF EXISTS clause prevents an error if the table does not exist. The optional database_name. prefix specifies the database where the table resides. If not specified, the current database is used. Therefore, the correct command to remove the table table_name from the database database_name and all of the data files associated with it is DROP TABLE database_name.table_name;. The other commands are either invalid syntax or would produce undesired results. Reference: Databricks - DROP TABLE

NEW QUESTION # 29
......

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

Databricks-Certified-Data-Analyst-Associate Exam Questions: Free PDF Download Recently Updated Questions: https://prep4sure.dumpstests.com/Databricks-Certified-Data-Analyst-Associate-latest-test-dumps.html