Premium

Dell EMC Data Science and BigData Certification Questions and Answers



Question : Data shown in the below image falls under which category?



 : Data shown in the below image falls under which category?
1. Semi-structured data

2. Structured data

3. Quasi-structured data

4. Unstructured data


Correct Answer : 1
Explanation: XML data falls under the semi-structured data category. Because they are having metadata associated with them like schema which can help you transform your data in a structured format. Once
its structure and format is defined you can query that data.




Question : Data shown in below image fall under which types of data category?


 :  Data shown in below image fall under which types of data category?
1. Semi-structured data

2. Structured data

3. Quasi-structured data

4. Unstructured data


Correct Answer : 2
Explanation: As data shown in the image is having well structure and can be easily queried and searched. Hence, it fall under structured data.




Question : Which of the following data are quasi-structured data?

 : Which of the following data are quasi-structured data?
1. A
2. B
3. C
4. D

Correct Answer : 3
Explanation: As you can see in the option, in search result some video files are shown. But these are to confuse you. As data shown are search results. Hence, they fall under quasi-structure data and not
under the unstructured data.


Related Questions


Question : Which of the following statement is correct with regards to factor data type in R?
A. Factor can be used to represent categorical data.
B. Factors can be ordered and unordered
C. Factors are integers
D. Factors can have any undefined new value in it.
E. Factors are characters

 : Which of the following statement is correct with regards to factor data type in R?
1. A,B,C
2. B,C,D
3. C,D,E
4. A,D,E
5. A,C,E


Question : You are working as a data scientists for a company which sale the car tyre in a country. Initially you have been given a data set with almost , rows. To apply your analytics you need location
information as well and you are provided with the 25,000 records with the location information which has 150 unique cities in that. Which of the following data structure from the R programming language best fit for
this column?

 : You are working as a data scientists for a company which sale the car tyre in a country. Initially you have been given a data set with almost , rows. To apply your analytics you need location
1. List

2. Array

3. Vector

4. Factor



Question : Which of the following are example of qualitative data?
A. Labels
B. Softness of a cloth
C. Interval
D. Ratio

 : Which of the following are example of qualitative data?
1. A,B
2. B,C
3. C,D
4. A,D
5. B,D


Question : Which of the following fall under the qualitative data?


 : Which of the following fall under the qualitative data?
1. Nominal and Ordinal

2. Nominal and Ratio

3. Ordinal and interval

4. Ratio and interval



Question : Suppose you have two populations called HEPop and HEPop. You need to check whether two populations are different from each other or not. Which of the following would help in this case?


 : Suppose you have two populations called HEPop and HEPop. You need to check whether two populations are different from each other or not. Which of the following would help in this case?
1. You would be using K-means clustering

2. You would be using logistic regression

3. You will be using Hypothesis testing

4. You will be using Linear Regression



Question : You have two populations like HEPop and HEPop, you need to find that both the populations are different from each other or not. Which of the following is correct Hypothesis in this case?


 : You have two populations like HEPop and HEPop, you need to find that both the populations are different from each other or not. Which of the following is correct Hypothesis in this case?
1. Null Hypothesis : mean of(HEPop1) = mean of (HEPop2)
Alternate Hypothesis: mean of (HEPop1) <> mean of (HEPop2)

2. Null Hypothesis : mean of(HEPop1) <> mean of (HEPop2)
Alternate Hypothesis: mean of (HEPop1) = mean of (HEPop2)

3. Null Hypothesis : mean of(HEPop1) <> mean of (HEPop2)
Alternate Hypothesis: mean of (HEPop1) <> mean of (HEPop2)

4. You cannot use mean of population for inferring the Population equality