Exam Details

  • Exam Code
    :E20-026
  • Exam Name
    :Enterprise Storage Networking Specialist Exam
  • Certification
    :EMC Specialist
  • Vendor
    :EMC
  • Total Questions
    :163 Q&As
  • Last Updated
    :Apr 26, 2025

EMC EMC Specialist E20-026 Questions & Answers

  • Question 131:

    Which functionality do regular expressions provide?

    A. text pattern matching

    B. underflow prevention

    C. increased numerical precision

    D. decreased processing complexity

  • Question 132:

    Which word or phrase completes the statement? A spreadsheet is to a data island as a centralized database for reporting is to a ________?

    A. Data Warehouse

    B. Data Repository

    C. Analytic Sandbox

    D. Data Mart

  • Question 133:

    What is one modeling or descriptive statistical function in MADlib that is typically not provided in a standard relational database?

    A. Linear regression

    B. Expected value

    C. Variance

    D. Quantiles

  • Question 134:

    In which phase of the data analytics lifecycle do Data Scientists spend the most time in a project?

    A. Discovery

    B. Data Preparation

    C. Model Building

    D. Communicate Results

  • Question 135:

    You are testing two new weight-gain formulas for puppies. The test gives the results:

    Control group: 1% weight gain Formula A. 3% weight gain Formula B. 4% weight gain A one-way ANOVA returns a p-value = 0.027

    What can you conclude?

    A. Either Formula A or Formula B is effective at promoting weight gain.

    B. Formula B is more effective at promoting weight gain than Formula A.

    C. Formula A and Formula B are both effective at promoting weight gain.

    D. Formula A and Formula B are about equally effective at promoting weight gain.

  • Question 136:

    If your intention is to show trends over time, which chart type is the most appropriate way to depict the data?

    A. Line chart

    B. Bar chart

    C. Stacked bar chart

    D. Histogram

  • Question 137:

    You are analyzing a time series and want to determine its stationarity. You also want to determine the

    order of autoregressive models.

    How are the autocorrelation functions used?

    A. ACF as an indication of stationarity,and PACF for the correlation between Xt and Xt-k not explained by their mutual correlation with X1 through Xk-1.

    B. PACF as an indication of stationarity,and ACF for the correlation between Xt and Xt-k not explained by their mutual correlation with X1 through Xk-1.

    C. ACF as an indication of stationarity,and PACF to determine the correlation of X1 through Xk-1.

    D. PACF as an indication of stationarity,and ACF to determine the correlation of X1 through Xk-1.

  • Question 138:

    What is an example of a null hypothesis?

    A. that a newly created model does not provide better predictions than the currently existing model

    B. that a newly created model provides a prediction of a null sample mean

    C. that a newly created model provides a prediction of a null population mean

    D. that a newly created model provides a prediction that will be well fit to the null distribution

  • Question 139:

    You have fit a decision tree classifier using 12 input variables. The resulting tree used 7 of the 12 variables, and is 5 levels deep. Some of the nodes contain only 3 data points. The AUC of the model is

    0.85. What is your evaluation of this model?

    A. The tree is probably overfit. Try fitting shallower trees and using an ensemble method.

    B. The AUC is high,and the small nodes are all very pure. This is an accurate model.

    C. The tree did not split on all the input variables. You need a larger data set to get a more accurate model.

    D. The AUC is high,so the overall model is accurate. It is not well-calibrated,because the small nodes will give poor estimates of probability.

  • Question 140:

    When would you prefer a Naive Bayes model to a logistic regression model for classification?

    A. When you are using several categorical input variables with over 1000 possible values each.

    B. When you need to estimate the probability of an outcome,not just which class it is in.

    C. When all the input variables are numerical.

    D. When some of the input variables might be correlated.

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