Online Data Mining Quiz Test
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 Warehouse and OLAP Technology
Introduction to Data Mining
Mining Frequent Patterns
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
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?
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
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
|Candidate Name: David Messi||Test Date: 28-May-2014|
|Test Name: Data Mining Test||Test Start Time: 13.30|
Score: 18 Out Of 20
|Tolerable Limit||Not acceptable|
|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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