After runningDESCRIBE EXTENDED accounts.customers;, the following was returned:

Now, a data analyst runs the following command:
DROP accounts.customers;
Which of the following describes the result of running this command?

1. A. Running SELECT * FROM delt
2. B. `dbfs:/stakeholders/customers` results in an error.
3. C. Running SELECT * FROM accounts.customers will return all rows in the table.
4. D. All files with the .customers extension are deleted.
5. E. The accounts.customers table is removed from the metastore, and the underlying data files are deleted.
6. F. The accounts.customers table is removed from the metastore, but the underlying data files are untouched.

Correct Answer: E
the accounts.customers table is an EXTERNAL table, which means that it is stored outside the default warehouse directory and is not managed by Databricks. Therefore, when you run the DROP command on this table, it only removes the metadata information from the metastore, but does not delete the actual data files from the file system. This means that you can still access the data using the location path (dbfs:/stakeholders/customers) or create another table pointing to the same location. However, if you try to query the table using its name (accounts.customers), you will get an error because the table no longer exists in the metastore. References: DROP TABLE | Databricks on AWS, Best practices for dropping a managed Delta Lake table - Databricks

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?

1. A. SELECT PRICE customer_spend, customer_units AS customer_price FROM customer_summary
2. B. SELECT price FROM customer_summary
3. C. SELECT function(price(customer_spend, customer_units)) AS customer_price FROM customer_summary
4. D. SELECT double(price(customer_spend, customer_units)) AS customer_price FROM customer_summary
5. E. SELECT price(customer_spend, customer_units) AS customer_price FROM customer_summary

Correct Answer: E
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. References:
✑ What are user-defined functions (UDFs)?
✑ User-defined scalar functions - SQL V

Which of the following is an advantage of using a Delta Lake-based data lakehouse over common data lake solutions?

1. A. ACID transactions
2. B. Flexible schemas
3. C. Data deletion
4. D. Scalable storage
5. E. Open-source formats

Correct Answer: A
A Delta Lake-based data lakehouse is a data platform architecture that combines the scalability and flexibility of a data lake with the reliability and performance of a data warehouse. One of the key advantages of using a Delta Lake-based data lakehouse over common data lake solutions is that it supports ACID transactions, which ensure data integrity and consistency. ACID transactions enable concurrent reads and writes, schema enforcement and evolution, data versioning and rollback, and data quality checks. These features are not available in traditional data lakes, which rely on file-based storage systems that do not support transactions. References:
✑ Delta Lake: Lakehouse, warehouse, advantages | Definition
✑ Synapse – Data Lake vs. Delta Lake vs. Data Lakehouse
✑ Data Lake vs. Delta Lake - A Detailed Comparison
✑ Building a Data Lakehouse with Delta Lake Architecture: A Comprehensive Guide

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?

1. A. Heatmap
2. B. IChoropleth
3. C. Word Cloud
4. D. Pivot Table
5. E. Sankey

Correct Answer: E
A Sankey diagram is a type of visualization that shows the flow of data between different nodes or categories. It is often used to represent the movement of users through a website, as it can show the paths they take, the sources they come from, the pages they visit, and the outcomes they achieve. A Sankey diagram consists of links and nodes, where the links represent the volume or weight of the flow, and the nodes represent the stages or steps of the flow. The width of the links is proportional to the amount of flow, and the color of the links can indicate different attributes or segments of the flow. A Sankey diagram can help identify the most common or popular user journeys, the bottlenecks or drop-offs in the flow, and the opportunities for improvement or optimization. References: The answer can be verified from Databricks documentation which provides examples and instructions on how to create Sankey diagrams using Databricks SQL Analytics and Databricks Visualizations. Reference links: Databricks SQL Analytics - Sankey Diagram, Databricks Visualizations - Sankey Diagram