Online Data Mining Quiz Test

Topics covered

Data Processing, Data Warehouse and OLAP Technology, Introduction to Data Mining, Data Preprocessing, Mining Frequent Patterns, Data Cleaning, Data Reduction, Data Mining Process, Data Integration and Transformation

  • MAQ (Multiple Answer Question)
  • MCQ (Multiple Choice Question)
  • Descriptive Question
  • White Board Simulator
  • Coding Simulator
  • Audio Question
  • Video Question
  • Case Study Question

Data Mining Quiz helps Recruiters & Hiring Managers to effectively assess the skills of the Data Mining analyst before an interview. Data Mining is the computational process of discovering patterns in a form of large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics and database systems. This Data Mining online test is designed to check the development and programming skills of Data Mining Developer - As per Industry Standards.

Data Mining Assessment Test contains questions on following Topics:
 

  • Data Processing

  • Data Warehouse and OLAP Technology

  • Introduction to Data Mining

  • Data Preprocessing

  • Mining Frequent Patterns

  • Data Cleaning

  • Data Reduction

  • Data Mining Process

  • Data Integration and Transformation 


This Data Mining knowledge test is designed & validated by our experienced subject matter experts (SME)s to evaluate the candidate’s knowledge about Data Mining basics before hiring. Using powerful reporting, you can have a detailed analysis of the test results to help you make a better hiring decision and predict the candidate’s performance.

The test contains MCQ's (Multiple Choice Questions), MAQ's (Multiple Answer Questions), Fill in the Blank, Descriptive, True or False.

This pre-employment test is useful for hiring:
  • Data Mining Analyst

  • Data Mining Specialist
  • Data Mining Consultant
  • Data Mining Expert

Test details:

This Data Mining Interview Test enables employers and recruiters to identify potential data Mining Consultant & Specialist by evaluating working skills and job readiness. For this reason, the emphasis is laid upon evaluating the knowledge of applied skills gained through real work experience, rather than theoretical knowledge.

Test Details: 30 minutes

20 Application Questions


The combination of Application questions helps to evaluate Technical as well as practical Skills of Candidates.

Data Mining Test

Question #1 of 3

When applying for a credit card, candidates may be asked to supply their driver’s license number. Candidates who do not have a driver’s license may naturally leave this field blank. Forms should allow candidates to fill in the blank field. Which field is more likely suitable to the credit card analogy above?

    • "Not allowed"

    • "Not available"

    • "Not applicable"

    • "Not open"

Question #2 of 3

I have a set of data to analyse the impact of staff salary on retention with my model specified thus:
Y = a+bX
X = staff salary (the predictor variable)
Y = staff salary (the predictor variable)
a and b are coefficients.

How can this model be used to approximate the data?

    • Correlation and ANOVA

    • Regression and log-linear models

    • Scatterplot and Covariance

    • Descriptive Statistics

Question #3 of 3

A data mining system should be able to produce a description summarizing the characteristics of customers who spend more than $1,000 a year at Fara Consulting. The result could be a general pro?le of the customers, such as they are 40–50 years old, employed, and have excellent credit ratings. The system should allow users to drill down on any dimension. Which one of the responses is less likely?

    • Such as on location in order to view these customers according to their type of availability

    • Such as on occupation in order to view these customers according to their type of employment

    • Such as on address in order to view these customers according to their type of apartment

    • Such as on occupation in order to view these customers according to their type of gender

SAMPLE REPORT
Candidate Name: David Messi Test Date: 28-May-2014
Test Name: Data Mining Test Test Start Time: 13.30

Score: 18 Out Of 20

Percentage: 90

Result: PASS

passing score image
SECTION PERFORMANCE
Section Name FAIL PASS
Data mining
Score: 18/20
STRENGTH AND WEAKNESS
Strength Data mining
Weakness -
* Note: If score <= 40 then its a Weakness. If score >= 80 then its a Strength.
ONLINE PROCTORING
0%
10 20 30 40 50 60 70 80 90 100%
Tolerable Limit Not acceptable
Window Violation: 0 | Time Violation: 0 secs
CANDIDATE DETAILS
Gender : Male Phone Number : +1-541-754-3010
Total Experience (Years) : 3 Total Experience (Months) : 5
Skill Set : Data mining Current Employer : Interview Mocha
Current Job Title : Solution Architect Current Salary : 600.00
Expected Salary : 1000000.00 Current Location : Chicago

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