Search test library by skills or roles
⌘ K

About the test:

The Data Mining Test evaluates candidates on their knowledge of data mining techniques, data preprocessing, association rule mining, classification, clustering, and data visualization using scenario-based MCQs. In addition to these key skills, the test also assesses a candidate's understanding of data warehousing, data cleaning, and big data technologies.

Covered skills:

  • Data Processing
  • Data Preprocessing
  • Data Cleaning
  • Data Mining Process
  • Data Warehouse and OLAP Technology
  • Mining Frequent Patterns
  • Data Reduction
  • Data Integration and Transformation

Try practice test
9 reasons why
9 reasons why

Adaface Data Mining Assessment Test is the most accurate way to shortlist Data Scientists



Reason #1

Tests for on-the-job skills

The Data Mining Test helps recruiters and hiring managers identify qualified candidates from a pool of resumes, and helps in taking objective hiring decisions. It reduces the administrative overhead of interviewing too many candidates and saves time by filtering out unqualified candidates at the first step of the hiring process.

The test screens for the following skills that hiring managers look for in candidates:

  • Ability to extract meaningful insights from large datasets
  • Proficiency in data modeling techniques
  • Understanding of ETL (Extract, Transform, Load) processes
  • Knowledge of data processing and analysis
  • Familiarity with data warehouse and OLAP technology
  • Ability to preprocess data for mining purposes
  • Experience with mining frequent patterns in datasets
  • Ability to clean and reduce data noise
  • Understanding of the data mining process
  • Competency in data integration and transformation
Reason #2

No trick questions

no trick questions

Traditional assessment tools use trick questions and puzzles for the screening, which creates a lot of frustration among candidates about having to go through irrelevant screening assessments.

View sample questions

The main reason we started Adaface is that traditional pre-employment assessment platforms are not a fair way for companies to evaluate candidates. At Adaface, our mission is to help companies find great candidates by assessing on-the-job skills required for a role.

Why we started Adaface
Try practice test
Reason #3

Non-googleable questions

We have a very high focus on the quality of questions that test for on-the-job skills. Every question is non-googleable and we have a very high bar for the level of subject matter experts we onboard to create these questions. We have crawlers to check if any of the questions are leaked online. If/ when a question gets leaked, we get an alert. We change the question for you & let you know.

How we design questions

These are just a small sample from our library of 10,000+ questions. The actual questions on this Data Mining Test will be non-googleable.

🧐 Question

Easy

Healthcare System
Data Integrity
Normalization
Referential Integrity
Try practice test
You are designing a data model for a healthcare system with the following requirements:
 image
A: A separate table for each entity with foreign keys as specified, and a DoctorPatient table linking Doctors to Patients.
B: A separate table for each entity with foreign keys as specified, without additional tables.
C: A combined PatientDoctor table replacing Patient and Doctor, and separate tables for Appointment and Prescription.
D: A separate table for each entity with foreign keys, and a PatientPrescription table to track prescriptions directly linked to patients.
E: A single table combining Patient, Doctor, Appointment, and Prescription into one.
F: A separate table for each entity with foreign keys as specified, and an AppointmentDetails table linking Appointments to Prescriptions.

Hard

ER Diagram and minimum tables
ER Diagram
Try practice test
Look at the given ER diagram. What do you think is the least number of tables we would need to represent M, N, P, R1 and R2?
 image
 image
 image

Medium

Normalization Process
Normalization
Database Design
Anomaly Elimination
Try practice test
Consider a healthcare database with a table named PatientRecords that stores patient visit information. The table has the following attributes:

- VisitID
- PatientID
- PatientName
- DoctorID
- DoctorName
- VisitDate
- Diagnosis
- Treatment
- TreatmentCost

In this table:

- Each VisitID uniquely identifies a patient's visit and is associated with one PatientID.
- PatientID is associated with exactly one PatientName.
- Each DoctorID is associated with a unique DoctorName.
- TreatmentCost is a fixed cost based on the Treatment.

Evaluating the PatientRecords table, which of the following statements most accurately describes its normalization state and the required actions for higher normalization?
A: The table is in 1NF. To achieve 2NF, remove partial dependencies by separating Patient information (PatientID, PatientName) and Doctor information (DoctorID, DoctorName) into different tables.
B: The table is in 2NF. To achieve 3NF, remove transitive dependencies by creating separate tables for Patients (PatientID, PatientName), Doctors (DoctorID, DoctorName), and Visits (VisitID, PatientID, DoctorID, VisitDate, Diagnosis, Treatment, TreatmentCost).
C: The table is in 3NF. To achieve BCNF, adjust for functional dependencies such as moving DoctorName to a separate Doctors table.
D: The table is in 1NF. To achieve 3NF, create separate tables for Patients, Doctors, and Visits, and remove TreatmentCost as it is a derived attribute.
E: The table is in 2NF. To achieve 4NF, address any multi-valued dependencies by separating Visit details and Treatment details.
F: The table is in 3NF. To achieve 4NF, remove multi-valued dependencies related to VisitID.

Medium

University Courses
ER Diagrams
Complex Relationships
Integrity Constraints
Try practice test
 image
Based on the ER diagram, which of the following statements is accurate and requires specific knowledge of the ER diagram's details?
A: A Student can major in multiple Departments.
B: An Instructor can belong to multiple Departments.
C: A Course can be offered by multiple Departments.
D: Enrollment records can link a Student to multiple Courses in a single semester.
E: Each Course must be associated with an Enrollment record.
F: A Department can offer courses without having any instructors.

Medium

Data Merging
Data Merging
Conditional Logic
Try practice test
A data engineer is tasked with merging and transforming data from two sources for a business analytics report. Source 1 is a SQL database 'Employee' with fields EmployeeID (int), Name (varchar), DepartmentID (int), and JoinDate (date). Source 2 is a CSV file 'Department' with fields DepartmentID (int), DepartmentName (varchar), and Budget (float). The objective is to create a summary table that lists EmployeeID, Name, DepartmentName, and YearsInCompany. The YearsInCompany should be calculated based on the JoinDate and the current date, rounded down to the nearest whole number. Consider the following initial SQL query:
 image
Which of the following modifications ensures accurate data transformation as per the requirements?
A: Change FLOOR to CEILING in the calculation of YearsInCompany.
B: Add WHERE e.JoinDate IS NOT NULL before the JOIN clause.
C: Replace JOIN with LEFT JOIN and use COALESCE(d.DepartmentName, 'Unknown').
D: Change the YearsInCompany calculation to YEAR(CURRENT_DATE) - YEAR(e.JoinDate).
E: Use DATEDIFF(YEAR, e.JoinDate, CURRENT_DATE) for YearsInCompany calculation.

Medium

Data Updates
Staging
Data Warehouse
Try practice test
Jaylo is hired as Data warehouse engineer at Affflex Inc. Jaylo is tasked with designing an ETL process for loading data from SQL server database into a large fact table. Here are the specifications of the system:
1. Orders data from SQL to be stored in fact table in the warehouse each day with prior day’s order data
2. Loading new data must take as less time as possible
3. Remove data that is more then 2 years old
4. Ensure the data loads correctly
5. Minimize record locking and impact on transaction log
Which of the following should be part of Jaylo’s ETL design?

A: Partition the destination fact table by date
B: Partition the destination fact table by customer
C: Insert new data directly into fact table
D: Delete old data directly from fact table
E: Use partition switching and staging table to load new data
F: Use partition switching and staging table to remove old data

Medium

SQL in ETL Process
SQL Code Interpretation
Data Transformation
SQL Functions
Try practice test
In an ETL process designed for a retail company, a complex SQL transformation is applied to the 'Sales' table. The 'Sales' table has fields SaleID, ProductID, Quantity, SaleDate, and Price. The goal is to generate a report that shows the total sales amount and average sale amount per product, aggregated monthly. The following SQL code snippet is used in the transformation step:
 image
What specific function does this SQL code perform in the context of the ETL process, and how does it contribute to the reporting goal?
A: The code calculates the total and average sales amount for each product annually.
B: It aggregates sales data by month and product, computing total and average sales amounts.
C: This query generates a daily breakdown of sales, both total and average, for each product.
D: The code is designed to identify the best-selling products on a monthly basis by sales amount.
E: It calculates the overall sales and average price per product, without considering the time dimension.

Medium

Trade Index
Index
Try practice test
Silverman Sachs is a trading firm and deals with daily trade data for various stocks. They have the following fact table in their data warehouse:
Table: Trades
Indexes: None
Columns: TradeID, TradeDate, Open, Close, High, Low, Volume
Here are three common queries that are run on the data:
 image
Dhavid Polomon is hired as an ETL Developer and is tasked with implementing an indexing strategy for the Trades fact table. Here are the specifications of the indexing strategy:

- All three common queries must use a columnstore index
- Minimize number of indexes
- Minimize size of indexes
Which of the following strategies should Dhavid pick:
A: Create three columnstore indexes: 
1. Containing TradeDate and Close
2. Containing TradeDate, High and Low
3. Container TradeDate and Volume
B: Create two columnstore indexes:
1. Containing TradeID, TradeDate, Volume and Close
2. Containing TradeID, TradeDate, High and Low
C: Create one columnstore index that contains TradeDate, Close, High, Low and Volume
D: Create one columnstore index that contains TradeID, Close, High, Low, Volume and Trade Date
🧐 Question🔧 Skill

Easy

Healthcare System
Data Integrity
Normalization
Referential Integrity

2 mins

Data Modeling
Try practice test

Hard

ER Diagram and minimum tables
ER Diagram

2 mins

Data Modeling
Try practice test

Medium

Normalization Process
Normalization
Database Design
Anomaly Elimination

3 mins

Data Modeling
Try practice test

Medium

University Courses
ER Diagrams
Complex Relationships
Integrity Constraints

2 mins

Data Modeling
Try practice test

Medium

Data Merging
Data Merging
Conditional Logic

2 mins

ETL
Try practice test

Medium

Data Updates
Staging
Data Warehouse

2 mins

ETL
Try practice test

Medium

SQL in ETL Process
SQL Code Interpretation
Data Transformation
SQL Functions

3 mins

ETL
Try practice test

Medium

Trade Index
Index

3 mins

ETL
Try practice test
🧐 Question🔧 Skill💪 Difficulty⌛ Time
Healthcare System
Data Integrity
Normalization
Referential Integrity
Data Modeling
Easy2 mins
Try practice test
ER Diagram and minimum tables
ER Diagram
Data Modeling
Hard2 mins
Try practice test
Normalization Process
Normalization
Database Design
Anomaly Elimination
Data Modeling
Medium3 mins
Try practice test
University Courses
ER Diagrams
Complex Relationships
Integrity Constraints
Data Modeling
Medium2 mins
Try practice test
Data Merging
Data Merging
Conditional Logic
ETL
Medium2 mins
Try practice test
Data Updates
Staging
Data Warehouse
ETL
Medium2 mins
Try practice test
SQL in ETL Process
SQL Code Interpretation
Data Transformation
SQL Functions
ETL
Medium3 mins
Try practice test
Trade Index
Index
ETL
Medium3 mins
Try practice test
Reason #4

1200+ customers in 75 countries

customers in 75 countries
Brandon

With Adaface, we were able to optimise our initial screening process by upwards of 75%, freeing up precious time for both hiring managers and our talent acquisition team alike!


Brandon Lee, Head of People, Love, Bonito

Try practice test
Reason #5

Designed for elimination, not selection

The most important thing while implementing the pre-employment Data Mining Test in your hiring process is that it is an elimination tool, not a selection tool. In other words: you want to use the test to eliminate the candidates who do poorly on the test, not to select the candidates who come out at the top. While they are super valuable, pre-employment tests do not paint the entire picture of a candidate’s abilities, knowledge, and motivations. Multiple easy questions are more predictive of a candidate's ability than fewer hard questions. Harder questions are often "trick" based questions, which do not provide any meaningful signal about the candidate's skillset.

Science behind Adaface tests
Reason #6

1 click candidate invites

Email invites: You can send candidates an email invite to the Data Mining Test from your dashboard by entering their email address.

Public link: You can create a public link for each test that you can share with candidates.

API or integrations: You can invite candidates directly from your ATS by using our pre-built integrations with popular ATS systems or building a custom integration with your in-house ATS.

invite candidates
Reason #7

Detailed scorecards & benchmarks

View sample scorecard
Try practice test
Reason #8

High completion rate

Adaface tests are conversational, low-stress, and take just 25-40 mins to complete.

This is why Adaface has the highest test-completion rate (86%), which is more than 2x better than traditional assessments.

test completion rate
Reason #9

Advanced Proctoring


Learn more

About the Data Mining Online Test

Why you should use Pre-employment Data Mining Test?

The Data Mining Test makes use of scenario-based questions to test for on-the-job skills as opposed to theoretical knowledge, ensuring that candidates who do well on this screening test have the relavant skills. The questions are designed to covered following on-the-job aspects:

  • Data processing and manipulation techniques
  • Knowledge of data warehousing and OLAP technology
  • Understanding the basics and concepts of data mining
  • Data preprocessing techniques and methods
  • Ability to mine frequent patterns in large datasets
  • Cleaning and handling dirty data
  • Data reduction techniques for efficient mining
  • Understanding and following the data mining process
  • Data integration and transformation skills
  • Ability to interpret and analyze mining results

Once the test is sent to a candidate, the candidate receives a link in email to take the test. For each candidate, you will receive a detailed report with skills breakdown and benchmarks to shortlist the top candidates from your pool.

What topics are covered in the Data Mining Test?

  • Data Preprocessing

    Data preprocessing involves preparing and cleaning the data before the actual mining process takes place. It includes tasks like removing noise, handling missing values, standardizing data, and transforming variables. Measuring this skill in the test helps evaluate a candidate's ability to preprocess data effectively, ensuring the quality and reliability of the mining results.

  • Mining Frequent Patterns

    Mining frequent patterns focuses on discovering recurring itemsets or sequences in a dataset. It involves techniques like market basket analysis and association rule mining. This skill should be measured in the test to assess a candidate's proficiency in identifying common patterns, which can be valuable for various applications such as recommendation systems and market analysis.

  • Data Cleaning

    Data cleaning is the process of identifying and correcting or removing errors, inconsistencies, and outliers in the dataset. It includes tasks like handling duplicate records, resolving inconsistencies, and dealing with noisy or irrelevant data. Measuring this skill in the test helps evaluate a candidate's ability to ensure data integrity and reliability, which is crucial for accurate mining results.

  • Data Reduction

    Data reduction involves techniques for reducing the size and dimensionality of the dataset without significantly losing relevant information. It aims to remove redundant or irrelevant features and transform the data into a more compact representation. Measuring this skill in the test helps evaluate a candidate's ability to optimize the data mining process by reducing computational complexity and improving efficiency.

  • Data Mining Process

    Data mining process encompasses the systematic steps involved in extracting meaningful patterns and insights from data. It includes tasks like data exploration, model selection, pattern evaluation, and result interpretation. Measuring this skill in the test helps evaluate a candidate's understanding of the overall data mining workflow and their ability to apply appropriate techniques at each stage.

  • Data Integration and Transformation

    Data integration and transformation involve consolidating data from various sources, resolving data conflicts, and transforming data into a unified format for analysis. It requires knowledge of data integration techniques, data mapping, and data transformation operations. Measuring this skill in the test helps evaluate a candidate's ability to effectively integrate and transform disparate data sources, ensuring consistency and accuracy in the mining process.

  • Full list of covered topics

    The actual topics of the questions in the final test will depend on your job description and requirements. However, here's a list of topics you can expect the questions for Data Mining Test to be based on.

    Data Processing
    Data Warehouse
    OLAP Technology
    Data Preprocessing
    Mining Frequent Patterns
    Data Cleaning
    Data Reduction
    Data Mining Process
    Data Integration
    Data Transformation
    Data Extraction
    Data Loading
    Data Modeling
    Data Analytics
    Supervised Learning
    Unsupervised Learning
    Association Rules
    Decision Trees
    Clustering
    Classification
    Data Visualization
    Data Exploration
    Big Data
    Predictive Modeling
    Pattern Recognition
    Text Mining
    Web Mining
    Social Network Analysis
    Feature Selection
    Dimensionality Reduction
    Outlier Detection
    Data Imputation
    Naive Bayes
    Support Vector Machines
    Neural Networks
    Genetic Algorithms
    Regression Analysis
    Time Series Analysis
    Spatial Data Mining
    Data Privacy
    Ethics in Data Mining
    Market Basket Analysis
    Association Rule Mining
    Sequential Pattern Mining
    Anomaly Detection
    Model Evaluation
    Overfitting
    Ensemble Methods
    Cross-validation
    Data Sampling
    Data Fusion
    Parallel and Distributed Data Mining
    Data Scalability
    Data Quality Assessment
    Data Profiling
    Feature Engineering
    Data Wrangling
Try practice test

What roles can I use the Data Mining Test for?

  • Data Scientist
  • Business Analyst
  • Data Analyst
  • Data Engineer
  • Database Administrator
  • Research Scientist

How is the Data Mining Test customized for senior candidates?

For intermediate/ experienced candidates, we customize the assessment questions to include advanced topics and increase the difficulty level of the questions. This might include adding questions on topics like

  • Proficiency in statistical analysis
  • Ability to implement various data mining algorithms
  • Knowledge of supervised and unsupervised learning techniques
  • Experience with decision tree algorithms
  • Understanding of association rule mining
  • Expertise in clustering techniques
  • Experience in classification and regression models
  • Proficiency in handling large-scale datasets
  • Familiarity with Big Data technologies
  • Expertise in data visualization and reporting
Singapore government logo

The hiring managers felt that through the technical questions that they asked during the panel interviews, they were able to tell which candidates had better scores, and differentiated with those who did not score as well. They are highly satisfied with the quality of candidates shortlisted with the Adaface screening.


85%
reduction in screening time

Data Mining Hiring Test FAQs

Can I combine multiple skills into one custom assessment?

Yes, absolutely. Custom assessments are set up based on your job description, and will include questions on all must-have skills you specify. Here's a quick guide on how you can request a custom test.

Do you have any anti-cheating or proctoring features in place?

We have the following anti-cheating features in place:

  • Non-googleable questions
  • IP proctoring
  • Screen proctoring
  • Web proctoring
  • Webcam proctoring
  • Plagiarism detection
  • Secure browser
  • Copy paste protection

Read more about the proctoring features.

How do I interpret test scores?

The primary thing to keep in mind is that an assessment is an elimination tool, not a selection tool. A skills assessment is optimized to help you eliminate candidates who are not technically qualified for the role, it is not optimized to help you find the best candidate for the role. So the ideal way to use an assessment is to decide a threshold score (typically 55%, we help you benchmark) and invite all candidates who score above the threshold for the next rounds of interview.

What experience level can I use this test for?

Each Adaface assessment is customized to your job description/ ideal candidate persona (our subject matter experts will pick the right questions for your assessment from our library of 10000+ questions). This assessment can be customized for any experience level.

Does every candidate get the same questions?

Yes, it makes it much easier for you to compare candidates. Options for MCQ questions and the order of questions are randomized. We have anti-cheating/ proctoring features in place. In our enterprise plan, we also have the option to create multiple versions of the same assessment with questions of similar difficulty levels.

I'm a candidate. Can I try a practice test?

No. Unfortunately, we do not support practice tests at the moment. However, you can use our sample questions for practice.

What is the cost of using this test?

You can check out our pricing plans.

Can I get a free trial?

Yes, you can sign up for free and preview this test.

I just moved to a paid plan. How can I request a custom assessment?

Here is a quick guide on how to request a custom assessment on Adaface.

customers across world
Join 1200+ companies in 75+ countries.
Try the most candidate friendly skills assessment tool today.
g2 badges
Ready to use the Adaface Data Mining Test?
Ready to use the Adaface Data Mining Test?
logo
40 min tests.
No trick questions.
Accurate shortlisting.
Terms Privacy Trust Guide

🌎 Pick your language

English Norsk Dansk Deutsche Nederlands Svenska Français Español Chinese (简体中文) Italiano Japanese (日本語) Polskie Português Russian (русский)
ada
Ada
● Online
✖️