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SnowPro Advanced: Data Scientist Practice Test

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killexams.com SnowFlake DSA-C02
SnowPro Advanced: Data Scientist
https://killexams.com/pass4sure/exam-detail/DSA-C02
Question: 750
What is a key advantage of using ensemble methods like Random Forest for multiclass classification?
1. They are faster than individual classifiers
2. They can handle missing values
3. They are less complex than single models
ey always outperform single models
wer: B
anation: Random Forest can handle missing values effectively, as it ca urrogate splits to make decisions even when some data points are miss ng it robust for multiclass problems.
stion: 751
When applying PCA, what is the purpose of the covariance matrix?
normalize the data
identify correlations between features create new features
define the target variable wer: B
anation: The covariance matrix is calculated to identify the correlatio
Th
Ans
Expl n
use s ing,
maki
Que
1. To
2. To
3. To
4. To
Ans
Expl ns
between features. PCA uses this matrix to determine the directions (principal components) that maximize variance in the data.
Question: 752
Which of the following is a key aspect of compliance considerations in data
science?
1. Lack of data documentation
2. Data encryption and access controls
3. Open access to all data
anation: Compliance considerations emphasize the importance of data yption and access controls to protect sensitive information and adhere
rotection regulations, ensuring data privacy and security.
stion: 753
ch of the following is NOT a benefit of using Snowflake for Data Scie ines?
utomatic scaling of resources igh concurrency
imited data storage options implified data sharing
wer: C
Inconsistent data handling procedures Answer: B
Expl
encr to
data p
Que
Whi nce
Pipel
1. A
2. H
3. L
4. S
Ans
Explanation: Limited data storage options is NOT a benefit of using Snowflake. In fact, Snowflake provides extensive storage options and capabilities, making it ideal for handling large volumes of data in Data Science Pipelines.
Question: 754
Which technique can be used to handle imbalanced datasets in classification tasks?
1. Data Augmentation
2. Cross-Validation
3. Under-sampling and Over-sampling
wer: C
anation: Under-sampling reduces the number of instances from the rity class, while over-sampling increases instances in the minority cla iming to balance class distributions for more effective model trainin
stion: 755
does the term "autocorrelation" refer to in regression analysis?
he correlation between two independent variables he correlation of residuals at different times
he relationship between predicted and actual values he effect of outliers on regression coefficients
wer: B
Feature Scaling Ans
Expl
majo ss,
both a g.
Que
What
1. T
2. T
3. T
4. T
Ans
Explanation: Autocorrelation refers to the correlation of residuals (errors) at different points in time. This is a concern in time series data and can violate the assumption of independence of errors in regression analysis.
Question: 756
In the context of time series forecasting, what does "seasonality" refer to?
1. Long-term trends in the data
2. Random fluctuations
3. Regular patterns that repeat over a known period
anation: Seasonality refers to regular, predictable patterns that occur a fic intervals in time series data, such as daily, monthly, or yearly uations.
stion: 757
ch of the following statements is true about PCA?
CA only works with categorical data.
CA transforms data to a new coordinate system. CA can only reduce dimensions to two.
CA is a supervised learning technique. wer: B
anation: PCA transforms data into a new coordinate system where the
Irregular variations Answer: C
Expl t
speci fluct
Que
Whi
1. P
2. P
3. P
4. P
Ans Expl
greatest variance by any projection lies on the first coordinate (principal component), followed by the second greatest variance on the second coordinate, and so forth.
Question: 758
What is a key advantage of the Snowflake Marketplace for data scientists?
1. Limited access to datasets.
2. Centralized access to diverse datasets.
3. High costs associated with data procurement.
anation:
y advantage of the Snowflake Marketplace for data scientists is centra ss to a diverse range of datasets. This accessibility enables data scienti elevant data quickly and efficiently, enhancing their analytical
bilities.
stion: 759
ch function would you use to convert a date to a string in a specific for nowflake?
O_DATE() O_STRING() O_CHAR() ORMAT_DATE()
Complicated data retrieval processes. Answer: B
Expl
A ke lized
acce sts to
find r capa
Que
Whi mat
in S
1. T
2. T
3. T
4. F
Answer: C
Explanation: The TO_CHAR() function is used to convert a date or timestamp to a string in a specified format, allowing for flexible formatting of date outputs in queries.
Question: 760
Which of the following techniques can be used for dimensionality reduction?
1. K-means clustering
2. Linear Regression
3. Principal Component Analysis (PCA)
wer: C anation:
cipal Component Analysis (PCA) is a widely used technique for nsionality reduction, transforming a high-dimensional dataset into a l nsional one while preserving as much variance as possible. This helps lify models and reduce overfitting.
stion: 761
ch command is used to delete a share in Snowflake?
ROP SHARE ELETE SHARE EMOVE SHARE HARE DROP
Decision Trees Ans
Expl Prin
dime ower-
dime simp
Que
Whi
1. D
2. D
3. R
4. S
Answer: A
Explanation: The command DROP SHARE is used to delete a share in Snowflake, removing the access granted to the shared objects and preventing further access by the specified accounts.
Question: 762
To update the "status" column of the "orders" table to "shipped" where the order ID is 123, which command should you use?
1. UPDATE orders SET status = 'shipped' WHERE order_id = 123;
HANGE orders SET status = 'shipped' WHERE order_id = 123; ET orders.status = 'shipped' WHERE order_id = 123;
wer: A
anation: The command UPDATE orders SET status = 'shipped' WHE r_id = 123; is the correct way to update a specific record in SQL. The ns do not follow standard SQL syntax.
stion: 763
ulticlass classification, what does "stratified sampling" ensure?
qual representation of all classes in training and test sets andom selection of samples without consideration of class election of only the majority class
limination of minority classes
MODIFY orders SET status = 'shipped' WHERE order_id = 123;
2. C
3. S
Ans
Expl RE
orde other
optio
Que
In m
1. E
2. R
3. S
4. E
Answer: A
Explanation: Stratified sampling ensures that each class is represented in the training and test sets in proportion to its occurrence in the entire dataset, which helps maintain class distribution and improves model performance.
Question: 764
What is the effect of including an irrelevant variable in a regression model concerning multicollinearity?
1. It reduces bias
can increase multicollinearity simplifies the model
wer: C
anation: Including irrelevant variables can introduce additional correla ng predictors, potentially increasing multicollinearity and complicatin el.
stion: 765
can you show the current user s role?
HOW CURRENT ROLE; ELECT CURRENT_ROLE(); ET CURRENT ROLE; ISPLAY ROLE;
It has no effect on multicollinearity
2. It
3. It
Ans
Expl tions
amo g the
mod
Que
How
1. S
2. S
3. G
4. D
Answer: B
Explanation: The command SELECT CURRENT_ROLE(); retrieves the role currently assigned to the user. This is the proper way to check the active role in SQL.
Question: 766
What is the default retention period for Time Travel in Snowflake if not explicitly configured?
1. 1 day
days days
wer: C
anation: If not explicitly configured, the default retention period for T el in Snowflake is 30 days, allowing users to access historical data ch within this time frame.
stion: 767
type of data preprocessing is typically performed before generating a
ata augmentation ata encoding
ata imputation
7 days
2. 30
3. 90
Ans
Expl ime
Trav anges
made
Que
What heat
map?
1. D
2. D
3. D
4. Data transformation Answer: C
Explanation:
Data imputation is often necessary before generating a heat map to handle missing values, ensuring that the dataset used for visualization is complete and
accurate. While data encoding (B) and transformation (D) are also important, imputation specifically addresses missing data issues.

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