Intelligent Informatica Data Quality Test

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Intelligent Informatica Data Quality Test - Quiz

Based on data integration network, Informatica Data Quality is used in the systems of small to big sized enterprises to easily access and cleanse data in any given source. Take this intelligent quiz to assess your knowledge of Informatica Data Quality.


Questions and Answers
  • 1. 

    To be of high quality, data must be...

    • A.

      Incoherent

    • B.

      Unambiguous

    • C.

      Complex

    • D.

      Inaccessible

    Correct Answer
    B. Unambiguous
    Explanation
    For data to be of high quality, it must be unambiguous. This means that the data should be clear and have a single interpretation. Ambiguous data can lead to confusion and errors in analysis and decision-making. Therefore, to ensure accuracy and reliability, it is important for data to be unambiguous.

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  • 2. 

    Data quality activities include the following except...

    • A.

      Rationalization

    • B.

      Validation

    • C.

      In-depth analysis

    • D.

      Skimming

    Correct Answer
    D. Skimming
    Explanation
    Skimming is not a data quality activity. Data quality activities involve processes such as rationalization, validation, and in-depth analysis to ensure that data is accurate, reliable, and consistent. Skimming, on the other hand, refers to quickly scanning or reading through information without detailed analysis or evaluation. Therefore, skimming is not a part of data quality activities.

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  • 3. 

    When data is of excellent quality, it...

    • A.

      Leads to insights that help the organization make better decisions

    • B.

      Creates a kind of friction

    • C.

      Narrows opportunities

    • D.

      Is cumbersome

    Correct Answer
    A. Leads to insights that help the organization make better decisions
    Explanation
    When data is of excellent quality, it leads to insights that help the organization make better decisions. This is because high-quality data is accurate, reliable, and relevant, allowing organizations to gain a deeper understanding of their operations, customers, and market trends. With these insights, organizations can identify patterns, trends, and opportunities that may have otherwise been overlooked. By leveraging the power of high-quality data, organizations can make informed decisions that drive growth, efficiency, and competitive advantage.

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  • 4. 

    Scrutinizing data is...

    • A.

      Never done

    • B.

      Done practically

    • C.

      Often frowned at

    • D.

      None of the above

    Correct Answer
    B. Done practically
    Explanation
    Scrutinizing data is done practically. This means that it is typically carried out in a practical or realistic manner. It implies that data is carefully examined, analyzed, and evaluated to gain insights or make informed decisions. It suggests that scrutinizing data is not just a theoretical or abstract concept, but rather a hands-on process that involves practical applications and real-world considerations.

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  • 5. 

    Data Quality Assurance is the process of...

    • A.

      Analysing data critically

    • B.

      Proffering solutions

    • C.

      Verifying the effectiveness of data

    • D.

      Storing data

    Correct Answer
    C. Verifying the effectiveness of data
    Explanation
    Data Quality Assurance is the process of verifying the effectiveness of data. This involves ensuring that the data is accurate, complete, and reliable. It includes checking for errors, inconsistencies, and discrepancies in the data, as well as validating its integrity and relevance. By verifying the effectiveness of data, organizations can ensure that the information they are using is trustworthy and can make informed decisions based on it.

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  • 6. 

    Aspects of data quality include the following except...

    • A.

      Relevance

    • B.

      Completeness

    • C.

      Accuracy

    • D.

      Redundancy

    Correct Answer
    D. Redundancy
    Explanation
    Data quality refers to the accuracy, completeness, and relevance of data. Redundancy, on the other hand, refers to the unnecessary duplication of data. It is not considered an aspect of data quality because redundant data can lead to confusion, increased storage requirements, and potential inconsistencies. Therefore, redundancy is the correct answer as it does not fall under the aspects of data quality.

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  • 7. 

    Relevance of data quality means that it could...

    • A.

      Correspond to what is being measured

    • B.

      Describe all aspect of the problem solved

    • C.

      Describe to a time, period, location that comprise and affect the subject

    • D.

      Be free of duplicate values

    Correct Answer
    C. Describe to a time, period, location that comprise and affect the subject
    Explanation
    The relevance of data quality means that the data should describe a specific time, period, and location that are relevant to the subject being studied. This ensures that the data accurately represents the context in which the subject exists and is affected by. By including this information, the data becomes more meaningful and useful for analysis and decision-making processes.

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  • 8. 

    Tools to use when data is not clean inside include the following except...

    • A.

      Extract

    • B.

      Transform

    • C.

      Prune

    • D.

      Load

    Correct Answer
    C. Prune
    Explanation
    Prune is not a tool used when data is not clean inside. The other three options, Extract, Transform, and Load, are commonly used tools in data cleaning processes. Extract involves retrieving data from various sources, Transform involves modifying and structuring the data, and Load involves loading the cleaned data into a database or a data warehouse. However, Prune is not a tool specifically used for data cleaning; it refers to the act of removing unnecessary or unwanted parts of something.

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  • 9. 

    Accuracy of data means that data will...

    • A.

      Pass spell checks

    • B.

      Checks

    • C.

      Spot checks

    • D.

      All of the above

    Correct Answer
    D. All of the above
    Explanation
    Accuracy of data refers to the correctness, precision, and reliability of the information. When data is accurate, it is free from errors, inconsistencies, and discrepancies. Therefore, it will pass spell checks, as it will have correct spellings. It will also pass checks, meaning that it will meet the required standards and criteria. Additionally, accuracy ensures that data can pass spot checks, which involve randomly selecting and reviewing a sample of data to ensure its accuracy. Therefore, the correct answer is "All of the above" as it encompasses all these aspects of data accuracy.

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  • 10. 

    Data being free of duplicate value means that it...

    • A.

      Is recent

    • B.

      Is fixed

    • C.

      Is not repeated

    • D.

      None of the above

    Correct Answer
    C. Is not repeated
    Explanation
    The given correct answer, "Is not repeated," suggests that when data is free of duplicate values, it means that there are no repeated or identical values present. This implies that each value in the data set is unique and does not occur more than once.

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Our quizzes are rigorously reviewed, monitored and continuously updated by our expert board to maintain accuracy, relevance, and timeliness.

  • Current Version
  • Mar 20, 2023
    Quiz Edited by
    ProProfs Editorial Team
  • Feb 25, 2018
    Quiz Created by
    Cripstwick
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