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killexams.com SnowFlake DSA-C02


SnowPro Advanced: Data Scientist


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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


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    use s ing,

    maki


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    1. To

    2. To

    3. To

    4. To


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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

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majo ss,

both a g.


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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


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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.