A SQL Dashboard was built for the supply chain team to monitor the inventory and product orders, but all of the timestamps displayed on the dashboards are showing in UTC format, so they requested to change the time zone to the location of New York. How would you approach resolving this issue?

• A.Move the workspace from Central US zone to East US Zone
• B.Change the timestamp on the delta tables to America/New_York format
• C.Change the spark configuration of SQL endpoint to format the timestamp to Ameri-ca/New_York
• D.Under SQL Admin Console, set the SQL configuration parameter time zone to Ameri-ca/New_York
• E.Add SET Timezone = America/New_York on every of the SQL queries in the dashboard.

Correct Answer: D

Explanation
The answer is, Under SQL Admin Console, set the SQL configuration parameter time zone to America/New_York Here are steps you can take this to configure, so the entire dashboard is changed without changing individual queries Configure SQL parameters To configure all warehouses with SQL parameters:
1.Click Settings at the bottom of the sidebar and select SQL Admin Console.
2.Click the SQL Warehouse Settings tab.
3.In the SQL Configuration Parameters textbox, specify one key-value pair per line. Sepa-rate the name of the parameter from its value using a space. For example, to ena-ble ANSI_MODE:
Graphical user interface, text, application Description automatically generated

Similarly, we can add a line in the SQL Configuration parameters
timezone America/New_York
SQL configuration parameters | Databricks on AWS

Comment: *

Name: *

Email: *

Verification: *

A new data engineer has started at a company. The data engineer has recently been added to the company's
Databricks workspace as [email protected]. The data engineer needs to be able to query the table
sales in the database retail. The new data engineer already has been granted USAGE on the database retail.
Which of the following commands can be used to grant the appropriate permissions to the new data engineer?

• A.GRANT USAGE ON TABLE [email protected] TO sales;
• B.GRANT SELECT ON TABLE sales TO [email protected];
• C.GRANT CREATE ON TABLE sales TO [email protected];
• D.GRANT USAGE ON TABLE sales TO [email protected];
• E.GRANT SELECT ON TABLE [email protected] TO sales;

Comment: *

Name: *

Email: *

Verification: *

What is the purpose of the bronze layer in a Multi-hop Medallion architecture?

• A.Copy of raw data, easy to query and ingest data for downstream processes.
• B.Powers ML applications
• C.Data quality checks, corrupt data quarantined
• D.Contain aggregated data that is to be consumed into Silver
• E.Reduces data storage by compressing the data

Correct Answer: A

Explanation
The answer is, copy of raw data, easy to query and ingest data for downstream processes, Medallion Architecture - Databricks Here are the typical role of Bronze Layer in a medallion architecture.
Bronze Layer:
1. Raw copy of ingested data
2. Replaces traditional data lake
3. Provides efficient storage and querying of full, unprocessed history of data
4. No schema is applied at this layer
Exam focus: Please review the below image and understand the role of each layer(bronze, silver, gold) in medallion architecture, you will see varying questions targeting each layer and its purpose.
Sorry I had to add the watermark some people in Udemy are copying my content.

Comment: *

Name: *

Email: *

Verification: *

Consider flipping a coin for which the probability of heads is p, where p is unknown, and our goa is to
estimate p. The obvious approach is to count how many times the coin came up heads and divide by the total
number of coin flips. If we flip the coin 1000 times and it comes up heads 367 times, it is very reasonable to
estimate p as approximately 0.367. However, suppose we flip the coin only twice and we get heads both times.
Is it reasonable to estimate p as 1.0? Intuitively, given that we only flipped the coin twice, it seems a bit
rash to conclude that the coin will always come up heads, and____________is a way of avoiding such rash
conclusions.

• A.Naive Bayes
• B.Laplace Smoothing
• C.Logistic Regression
• D.Linear Regression

Comment: *

Name: *

Email: *

Verification: *

Which of the following two options are supported in identifying the arrival of new files, and incre-mental data from Cloud object storage using Auto Loader?

• A.Directory listing, File notification
• B.Checking pointing, watermarking
• C.Writing ahead logging, read head logging
• D.File hashing, Dynamic file lookup
• E.Checkpointing and Write ahead logging

Comment: *

Name: *

Email: *

Verification: *