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Dell EMC Data Science Associate Certification Questions and Answers (Dumps and Practice Questions)



Question : Which word or phrase completes the statement? Business Intelligence is to monitoring trends as
Data Science is to ________ trends.
: Which word or phrase completes the statement? Business Intelligence is to monitoring trends as
1. Predicting
2. Discarding
3. Driving
4. Optimizing

Correct Answer : 1
Explanation: Data Science is different than the traditional Business Analytics in some key areas. For example, data science

uses predictive and prescriptive analytics to predict what might happen using probabilities and confidence levels, not just report tools to report on what did happen.
Note: when we're dealing with historical data, there is a strong desire and need for the data to be 100% accurate. If you have your financial results wrong for the past quarter, folks are likely to go to jail. However predicting performance for the next quarter is usually measured in probabilities and confidence levels (e.g., "There is a 95% confidence that our revenues will come in next quarter between $200M to $212M).
is used for dealing with and mitigating the uncertainty in the data. It uses several analytic and visualization techniques to understand where uncertainty may lay in the data, and then uses data transformation techniques to massage the data into a workable form - not perfect, but again not necessary when dealing with probabilities and not absolutes.
is able to create as-needed data transformations (versus the traditional ETL process) to put the data into a format so that it can be combined with other data sources in search in insights about customers, products and operations.




Question : Consider a scale that has five () values that range from "not important" to "very important". Which
data classification best describes this data?
: Consider a scale that has five () values that range from
1. Nominal
2. Real
3. Ratio
4. Ordinal


Correct Answer : 4
Explanation: Ordinal Data: The next level higher of data classification than nominal data. Numerical data where number is assigned to represent a qualitative description similar to nominal data. However, these numbers can be arranged to represent worst to best or vice-versa. Ordinal data is a form of discrete data and should apply nonparametric test to analyze.
ratings provided on a FMEA for Severity, Occurrence, and Detection
DETECTION
1 = detectable every time
5 = detectable about 50% of the time
10 = not detectable at all
(All whole numbers from 1 - 10 represent levels of detection capability that are provided by team, customer, standards, or law)

classifying households as low income, middle-income, and high income
Nominal and ordinal data are from imprecise measurements and are referred to as non metric data, sometime referred to as qualitative data.
Ordinal data is also round when ranking sports teams, ranking the best cities to live, most popular beaches, and survey questionnaires.

3. Interval Data:
The next higher level of data classification. Numerical data where the data can be arranged in a order and the differences between the values are meaningful but not necessarily a zero point. Interval data can be both continuous and discrete. Zero degrees Fahrenheit does not mean it is the lowest point on the scale, it is just another point on the scale.
The lowest appropriate level for the mean is interval data.
Parametric AND nonparametric statistical techniques can be used to analyze interval data.
Examples in temperature readings, percentage change in performance of machine, and dollar change in price of oil/gallon.

4. Ratio Data:
Similar to interval data EXCEPT has a defined absolute zero point and is the highest level of data measurement. Ratio data can be both continuous and discrete.
Ratio level data has the highest level of usage and can be analyzed in more ways than the other three types of data.
Interval data and ratio data are considered metric data, also called quantitative data.






Question : Which key role for a successful analytic project can provide business domain expertise with a
deep understanding of the data and key performance indicators?
: Which key role for a successful analytic project can provide business domain expertise with a
1. Business User
2. Project Sponsor
3. Project Manager
4. Business Intelligence Analyst
5. None of above

Correct Answer : 4

Explanation: Data Science is different than the traditional Business Analytics in some key areas. For example, data science

uses predictive and prescriptive analytics to predict what might happen using probabilities and confidence levels, not just report tools to report on what did happen.
Note: when we're dealing with historical data, there is a strong desire and need for the data to be 100% accurate. If you have your financial results wrong for the past quarter, folks are likely to go to jail. However predicting performance for the next quarter is usually measured in probabilities and confidence levels (e.g., "There is a 95% confidence that our revenues will come in next quarter between $200M to $212M).
is used for dealing with and mitigating the uncertainty in the data. It uses several analytic and visualization techniques to understand where uncertainty may lay in the data, and then uses data transformation techniques to massage the data into a workable form - not perfect, but again not necessary when dealing with probabilities and not absolutes.
is able to create as-needed data transformations (versus the traditional ETL process) to put the data into a format so that it can be combined with other data sources in search in insights about customers, products and operations.






Related Questions

Question : Your colleague, who is new to Hadoop, approaches you with a question. They want to know how
best to access their data. This colleague has a strong background in data flow languages and
programming.
Which query interface would you recommend?

 : Your colleague, who is new to Hadoop, approaches you with a question. They want to know how
1. Hive
2. Pig
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4. HBase



Question : The web analytics team uses Hadoop to process access logs. They now want to correlate this
data with structured user data residing in a production single-instance JDBC database. They
collaborate with the production team to import the data into Hadoop. Which tool should they use?
 : The web analytics team uses Hadoop to process access logs. They now want to correlate this
1. Chukwa
2. Sqoop
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4. Flume




Question : What does the R code
z <- f[1:10, ]
do?

 : What does the R code
1. Assigns the 1st 10 columns of the 1st row of f to z
2. Assigns a sequence of values from 1 to 10 to z
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4. Assigns the first 10 rows of f to the vector z




Question : In R, functions like plot() and hist() are known as what?
 : In R, functions like plot() and hist() are known as what?
1. generic functions
2. virtual methods
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4. generic methods





Question : Review the following code:
SELECT pn, vn, sum(prc*qty)
FROM sale
GROUP BY CUBE(pn, vn)
ORDER BY 1, 2, 3;
Which combination of subtotals do you expect to be returned by the query?

 : Review the following code:
1. (pn, vn)
2. ( (pn, vn), (pn) )
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4. ( (pn, vn) , (pn), (vn) , ( ) )



Question : In MADlib what does MAD stand for?

 : In MADlib what does MAD stand for?
1. Machine Learning, Algorithms for Databases
2. Mathematical Algorithms for Databases
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4. Modular, Accurate, Dependable