Question 1

You have developed a SAS Viya application that generates several data visualizations. The visualizations need to be updated periodically based on user interactions. What is the best practice for managing the data and scripts for these visualizations?

Options :

A : Maintain the data and scripts on the server-side, and utilize server processing to update visualizations.

B : Store the scripts on the client-side and push them to the server whenever an update is required.

C : Keep the data on the client-side and transfer it to the server every time a visualization update is triggered.

D : Store visualization scripts on the client-side for easier debugging, and use AJAX calls to pull data from the server as needed.

Answer: A

Question 2

You are using the SIMPLE action set in a data analysis task and want to perform a data transformation by applying a mathematical formula to a variable in your dataset. Which action would allow you to create a new variable with these transformed values?

Options :

A : simple.transmute

B : simple.compute

C : simple.modify

D : simple.impute

Answer: A

Question 3

A data analyst needs to load a data set named 'sales_data' into the CAS (Cloud Analytic Services) environment to perform data analysis using SAS Viya. The 'sales_data' is currently stored in the 'my_data' library. Which of the following LOAD CASDATA= statement options would correctly load the dataset into the CAS server so it can be accessed using the default casuser library?

Options :

A : load casdata=sales_data casout=casuser;

B : caslib mylib data='my_data.sales_data' casout=casuser;

C : load data=my_data.sales_data casout=casuser;

D : load casdata=my_data.sales_data casout=casuser;

Answer: D

Question 4

When analyzing the time between customer purchases, a data analyst needs to extract the month from a date variable 'purchase_date' in the SAS Viya environment. Which function can be appropriately used to extract the month component from the date?

Options :

A : `DATEPART()`

B : `MONTH()`

C : `DAY()`

D : `EXTRACT()`

Answer: B

Question 5

You are designing an algorithm that will perform a series of matrix multiplication operations for a large-scale machine learning application. Which processing technique would likely yield a better performance given the computational requirements of matrix multiplication in this context, and why?

Options :

A : Serial processing, because matrix multiplication operations are inherently sequential.

B : Parallel processing, because matrix multiplication is computationally demanding and can be effectively distributed among processors.

C : Serial processing, because parallel processing incurs a synchronization overhead that negates the benefits of distributing the matrix multiplication tasks.

D : Parallel processing, because it avoids the overhead of context switching associated with serial processing.

Answer: B

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