Informatica Data Quality Online Test

Q: What are the main Informatica tests?

We offer several related tests: Informatica Online Test Informatica MDM Test Informatica B2B Data Exchange Test

The Informatica Data Quality online test evaluates a candidate's knowledge and skills in various aspects of data quality management. It covers topics such as data profiling, data cleansing, data standardization, duplicate detection, data monitoring, data validation, data enrichment, data governance, and data integration.

Covered skills:

Data Masking
Data Subset
Data Generation
Rule Simulator
Sequence Data Generation
Dictionary Data Generation
Data Quality
Data Profiling
Data Cleansing
Data Standardization
Duplicate Detection
Data Validation
Data Enrichment

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About the Informatica Data Quality Test

The Informatica Data Quality Online 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:

Able to perform Data Masking to protect sensitive information
Capable of generating realistic and representative Data Subsets
Proficient in generating large volumes of realistic test data using Data Generation techniques
Able to simulate and test complex data validation rules using Rule Simulator
Knowledge of generating sequential data using Sequence Data Generation
Familiarity with creating test data based on dictionary values using Dictionary Data Generation
Skilled in identifying and resolving data quality issues using Data Quality tools
Capable of profiling data to understand its structure, content, and completeness using Data Profiling techniques
Experienced in cleansing and transforming data to improve its quality
Knowledge of standardizing data to ensure consistency and compliance
Competent in detecting and handling duplicate records in data sets
Able to validate data against predefined rules and criteria
Proficient in enriching data with additional information or attributes

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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.

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Why you should use Pre-employment Informatica Data Quality Online Test?

The Informatica Data Quality 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 masking techniques to protect sensitive information
Creating smaller, representative subsets of larger datasets
Ability to create realistic test data for various scenarios
Proficiency in simulating and testing data quality rules to ensure accuracy
Skill in generating sequential or ordered test data
Ability to generate test data based on a predefined dictionary
Understanding of data quality concepts and techniques
Skill in identifying and correcting errors or inconsistencies in data
Proficiency in applying standardization rules to ensure consistent data

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 Informatica Data Quality Online Test?

Data Masking: Data masking is the process of replacing sensitive information with fictitious data, while preserving the overall structure, usability, and functionality of the original data. This skill should be measured in the test to assess the candidate's ability to protect sensitive data and ensure compliance with data security regulations.

Data Subset: Data subset refers to the process of creating a smaller, representative sample of a larger dataset. This skill should be measured in the test to evaluate the candidate's proficiency in extracting relevant subsets of data for analysis or testing purposes, which can help optimize performance and reduce resource requirements.

Data Generation: Data generation involves creating synthetic data that mimics real-world data. This skill should be measured in the test to assess the candidate's capability to generate large volumes of test data for various scenarios, such as performance testing, without relying on production data.

Rule Simulator: A rule simulator is a tool used to test and validate data quality rules and their impact on datasets. This skill should be measured in the test to evaluate the candidate's proficiency in simulating and verifying data quality rules, ensuring the accuracy, completeness, and validity of data.

Sequence Data Generation: Sequence data generation involves generating sequential values, such as unique identifiers or timestamps, in a specific order. This skill should be measured in the test to assess the candidate's ability to generate ordered sequences of data, which can be useful for maintaining data integrity and consistency in various applications.

Dictionary Data Generation: Dictionary data generation is the process of creating data based on predefined lists or dictionaries containing specific values. This skill should be measured in the test to evaluate the candidate's proficiency in generating data that adheres to predefined standards or criteria, facilitating data analysis and comparisons.

Data Quality: Data quality refers to the level of accuracy, completeness, consistency, and reliability of data. This skill should be measured in the test to assess the candidate's understanding of data quality concepts and their ability to identify and address data quality issues, ensuring the reliability and usability of data within an organization.

Data Profiling: Data profiling involves analyzing and understanding the structure, content, and quality of data. This skill should be measured in the test to evaluate the candidate's expertise in accurately assessing data quality, identifying data anomalies, and providing insight into data patterns, which is crucial for making informed data-driven decisions.

Data Cleansing: Data cleansing is the process of identifying and correcting erroneous, incomplete, or irrelevant data. This skill should be measured in the test to assess the candidate's ability to identify and rectify data quality issues, ensuring data accuracy, consistency, and integrity prior to analysis or integration with other systems.

Data Standardization: Data standardization involves transforming data into a consistent and predefined format, typically conforming to specific rules or guidelines. This skill should be measured in the test to evaluate the candidate's proficiency in converting data into a uniform format, facilitating data integration, comparability, and efficient data management.

Duplicate Detection: Duplicate detection is the process of identifying and removing duplicate records within a dataset. This skill should be measured in the test to assess the candidate's ability to develop algorithms or techniques for detecting and eliminating duplicate data, enhancing data accuracy, and reducing redundancy.

Data Validation: Data validation is the process of ensuring that data adheres to predefined rules, constraints, or requirements. This skill should be measured in the test to evaluate the candidate's expertise in validating data against specified criteria, detecting errors or inconsistencies, and ensuring data reliability, integrity, and adherence to business rules.

Data Enrichment: Data enrichment involves enhancing existing data by adding additional information, such as demographics, geolocation, or external datasets. This skill should be measured in the test to assess the candidate's proficiency in augmenting data with valuable insights, improving data completeness, accuracy, and overall quality for better decision-making and analysis.

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 Informatica Data Quality Test to be based on.

Data Masking

Sensitive Data Protection

Data Subset Generation

Test Data Generation

Data Validation Rules

Complex Rule Simulation

Sequential Data Generation

Dictionary Data Generation

Data Quality

Data Profiling

Data Cleansing

Data Standardization

Duplicate Detection

Data Validation

Data Enrichment

Data Quality Assessment

Data Quality Metrics

Data Profiling Methods

Data Cleansing Techniques

Data Lineage Analysis

Data Anomaly Detection

Data Quality Dashboards

Data Quality Dimensions

Data Matching Algorithms

Data Standardization Rules

Data Validation Techniques

Data Enrichment Methods

Data Masking Strategies

Data Subset Techniques

Data Generation Algorithms

Rule Simulation Scenarios

Sequence Data Generation Patterns

Dictionary Data Generation Sources

Duplicate Detection Algorithms

Data Quality Frameworks

Data Profiling Tools

Data Cleansing Software

Data Standardization Libraries

Data Validation Tools

Data Enrichment APIs

Data Masking Best Practices

Data Subset Optimization

Data Generation Performance

Rule Simulation Accuracy

Sequence Data Generation Efficiency

Dictionary Data Generation Customization

Duplicate Detection Precision

Data Validation Robustness

Data Enrichment Integration

Data Masking Regulations

Data Profiling Automation

Data Cleansing Databases

Data Standardization Models

Data Validation Frameworks

Data Enrichment Strategies

What roles can I use the Informatica Data Quality Online Test for?

Informatica Data Quality Developer
ETL Developer - Informatica/Data Quality
Informatica Data Quality Senior Analyst
Informatica Cloud Data Quality (CDQ) Consultant
Informatica Data Quality Application Developer

How is the Informatica Data Quality Online 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

Identify and handle duplicate records in a dataset
Validating data against predefined rules or criteria
Enhance existing data with additional information
Data governance principles and practices
Integrating data from multiple sources
Design and maintain data warehousing solutions
Understanding of ETL processes and tools
Skill in writing complex database queries and scripts

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Have questions about the Informatica Data Quality Hiring Test?

What is the Informatica Data Quality Test?

The Informatica Data Quality Test evaluates a candidate's skills in various data quality processes such as Data Masking, Data Profiling, and Data Cleansing. Recruiters use this test to find experts who can ensure high-quality data management practices.

Can I combine Informatica Data Quality Test with ETL questions?

Yes, recruiters can request a custom test that includes both Informatica Data Quality and ETL skills. For more details on ETL assessments, check out our ETL Online Test.

What skills are assessed for senior roles in this test?

Senior roles assessment includes identifying and handling duplicates, validating data, enhancing existing data, and understanding data governance principles. It also covers ETL processes, writing complex queries, and maintaining data warehousing solutions.

How to use Informatica Data Quality Test in my hiring process?

We recommend using this test as a pre-screening tool. Add a link to the test in your job post or invite candidates via email. This helps to find skilled candidates earlier in your recruitment process.

What are the main Informatica tests?

We offer several related tests:

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.

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Along with scorecards that report the performance of the candidate in detail, you also receive a comparative analysis against the company average and industry standards.

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