Snowflake DSA-C02 Certification Exam Sample Questions

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Snowflake DSA-C02 Sample Questions:

01. As Data Scientist looking out to use Reader account, Which ones are the correct considerations about Reader Accounts for Third-Party Access?
a) Data sharing is only possible between Snowflake accounts.
b) Each reader account belongs to the provider account that created it.
c) Users in a reader account can query data that has been shared with the reader account, but cannot perform any of the DML tasks that are allowed in a full account, such as data loading, insert, update, and similar data manipulation operations.
d) Reader accounts (formerly known as "read-only accounts") provide a quick, easy, and cost- effective way to share data without requiring the consumer to become a Snowflake customer.
 
02. You previously trained a model using a training dataset. You want to detect any data drift in the new data collected since the model was trained. What should you do?
a) Retrained your training dataset after correcting data outliers & no need to introduce new data.
b) Create a new dataset using the new data and a timestamp column and create a data drift monitor that uses the training dataset as a baseline and the new dataset as a target.
c) Create a new version of the dataset using only the new data and retrain the model.
d) Add the new data to the existing dataset and enable Application Insights for the service where the model is deployed.
 
03. Consider a data frame df with 10 rows and index [ 'r1', 'r2', 'r3', 'row4', 'row5', 'row6', 'r7', 'r8', 'r9', 'row10']. What does the expression g = df.groupby(df.index.str.len()) do?
a) Groups df based on index values
b) Groups df based on index strings
c) Groups df based on length of each index value
d) Data frames cannot be grouped by index values. Hence it results in Error.
 
04. Secure Data Sharing do not let you share which of the following selected objects in a database in your account with other Snowflake accounts?
a) Sequences
b) Tables
c) External tables
d) Secure UDFs
 
05. Performance metrics are a part of every machine learning pipeline, Which ones are not the performance metrics used in the Machine learning?
a) AU-ROC
b) Root Mean Squared Error (RMSE)
c) AUM
d) R (R-Squared)
 
06. Skewness of Normal distribution is ________.
a) Negative
b) 0
c) Positive
d) Undefined
 
07. How do you handle missing or corrupted data in a dataset?
a) Drop missing rows or columns
b) Replace missing values with mean/median/mode
c) Assign a unique category to missing values
d) All of the above
 
08. Which are the following additional Metadata columns Stream contains that could be used for creating Efficient Data science Pipelines & helps in transforming only the New/Modified data only?
a) METADATA$ACTION
b) METADATA$FILE_ID
c) METADATA$ISUPDATE
d) METADATA$DELETE
e) METADATA$ROW_ID
 
09. In a simple linear regression model (One independent variable), If we change the input variable by 1 unit. How much output variable will change?
a) no change
b) by intercept
c) by its slope
d) by 1
 
10. Which type of Machine learning Data Scientist generally used for solving classification and regression problems?
a) Unsupervised
b) Reinforcement Learning
c) Instructor Learning
d) Supervised
e) Regression Learning

Answers:

Question: 01
Answer: c		 Question: 02
Answer: b		 Question: 03
Answer: c		 Question: 04
Answer: a		 Question: 05
Answer: c
Question: 06
Answer: b		 Question: 07
Answer: d		 Question: 08
Answer: a, c, e		 Question: 09
Answer: c		 Question: 10
Answer: d

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