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Databricks Databricks-Certified-Data-Analyst-Associate Exam Dumps - Pass Exam With Brilliant Score

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

Topic
Details

Topic 1

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 2

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.

Topic 3

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 4

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 contrast MERGE INTO, INSERT TABLE, and COPY INTO. Lastly, this topic focuses on creating and applying UDFs in common scaling scenarios.

Topic 5

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.

Databricks Certified Data Analyst Associate Exam Sample Questions (Q59-Q64):

NEW QUESTION # 59
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 double(price(customer_spend, customer_units)) AS customer_price FROM customer_summary
C. SELECT PRICE customer_spend, customer_units AS customer_price FROM customer_summary
D. SELECT price FROM customer_summary
E. SELECT function(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 # 60
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. DROP TABLE table_name FROM database_name;
B. DROP TABLE database_name.table_name;
C. DROP DATABASE database_name;
D. DELETE TABLE table_name FROM database_name;
E. DELETE TABLE database_name.table_name;

Answer: B

NEW QUESTION # 61
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. There is no default. The user must choose a visualization type.
B. Line Chart
C. Violin Chart
D. Histogram
E. IBar Chart

Answer: E

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 # 62
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. Set a refresh schedule for the dashboard and enter the client's email address in the "Subscribers" box.
B. Download a PNG file of the visualizations in the dashboard and share them with the client.
C. Take a screenshot of the dashboard and share it with the client.
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 # 63
Which of the following benefits of using Databricks SQL is provided by Data Explorer?

A. It can be used to view metadata and data, as well as view/change permissions.
B. It can be used to produce dashboards that allow data exploration.
C. It can be used to run UPDATE queries to update any tables in a database.
D. It can be used to make visualizations that can be shared with stakeholders.
E. It can be used to connect to third party Bl cools.

Answer: A

Explanation:
Data Explorer is a user interface that allows you to discover and manage data, schemas, tables, models, and permissions in Databricks SQL. You can use Data Explorer to view schema details, preview sample data, and see table and model details and properties. Administrators can view and change owners, and admins and data object owners can grant and revoke permissions1. Reference: Discover and manage data using Data Explorer

NEW QUESTION # 64
......

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