The stakeholders.customers table has 15 columns and 3,000 rows of data. The following command is run:

After runningSELECT * FROM stakeholders.eur_customers, 15 rows are returned. After the command executes completely, the user logs out of Databricks.
After logging back in two days later, what is the status of thestakeholders.eur_customersview?

1. A. The view remains available and SELECT * FROM stakeholders.eur_customers will execute correctly.
2. B. The view has been dropped.
3. C. The view is not available in the metastore, but the underlying data can be accessed with SELECT * FROM delt
4. D. `stakeholders.eur_customers`.
5. E. The view remains available but attempting to SELECT from it results in an empty result set because data in views are automatically deleted after logging out.
6. F. The view has been converted into a table.

Correct Answer: B
The command you sent creates a TEMP VIEW, which is a type of view that is only visible and accessible to the session that created it. When the session ends or the user logs out, the TEMP VIEW is automatically dropped and cannot be queried anymore. Therefore, after logging back in two days later, the status of the stakeholders.eur_customers view is that it has been dropped and SELECT * FROM stakeholders.eur_customers will result in an error. The other options are not correct because:
✑ A. The view does not remain available, as it is a TEMP VIEW that is dropped when the session ends or the user logs out.
✑ C. The view is not available in the metastore, as it is a TEMP VIEW that is not registered in the metastore. The underlying data cannot be accessed with SELECT * FROM delta. stakeholders.eur_customers, as this is not a valid syntax for querying a Delta Lake table. The correct syntax would be SELECT * FROM delta.dbfs:/stakeholders/eur_customers, where the location path is enclosed in backticks. However, this would also result in an error, as the TEMP VIEW does not write any data to the file system and the location path does not exist.
✑ D. The view does not remain available, as it is a TEMP VIEW that is dropped when the session ends or the user logs out. Data in views are not automatically deleted after logging out, as views do not store any data. They are only logical representations of queries on base tables or other views.
✑ E. The view has not been converted into a table, as there is no automatic conversion between views and tables in Databricks. To create a table from a view, you need to use a CREATE TABLE AS statement or a similar
command. References: CREATE VIEW | Databricks on AWS, Solved: How do temp views actually work? - Databricks - 20136, temp tables in Databricks - Databricks - 44012, Temporary View in Databricks - BIG DATA PROGRAMMERS, Solved: What is the difference between a Temporary View an ??

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?

1. A. As an exact substitute with the same level of functionality
2. B. As a substitute with less functionality
3. C. As a complete replacement with additional functionality
4. D. As a complementary tool for professional-grade presentations
5. E. As a complementary tool for quick in-platform Bl work

Correct Answer: E
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. References: Databricks SQL, Connecting Applications and BI Tools to Databricks SQL, Databricks integrations overview, Databricks SQL: Delivering a Production SQL Development Experience on the Lakehouse

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?

1. A. Violin Chart
2. B. Line Chart
3. C. IBar Chart
4. D. Histogram
5. E. There is no defaul
6. F. The user must choose a visualization type.

Correct Answer: C
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. References: Visualization in Databricks SQL, Visualization types

A data analyst runs the following command: SELECT age, country
FROM my_table
WHERE age >= 75 AND country = 'canada';
Which of the following tables represents the output of the above command?
A)

B)

C)

D)

E)

1. A. Option A
2. B. Option B
3. C. Option C
4. D. Option D
5. E. Option E

Correct Answer: E
The SQL query provided is designed to filter out records from ??my_table?? where the age is 75 or above and the country is Canada. Since I can??t view the content of the links provided directly, I need to rely on the image attached to this question for context. Based on that, Option E (the image attached) represents a table with columns ??age?? and ??country??, showing records where age is 75 or above and country is Canada. References: The answer can be inferred from understanding SQL queries and their outputs as per Databricks documentation: Databricks SQL