Dt pH II Practice 1

95 Questions | Total Attempts: 54

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Practice Test Quizzes & Trivia

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Questions and Answers
  • 1. 
    Data when processed becomes Information
    • A. 

      True

    • B. 

      False

  • 2. 
    The best practice in data quality is 
    • A. 

      Fixing data quality issues in ETL

    • B. 

      Fixing data quality issues in ODS

    • C. 

      Fixing data quality issues in Source

    • D. 

      Fixing data quality issues in DW

  • 3. 
    Evaluate data quality before building a fully fledged data ware house
    • A. 

      True

    • B. 

      False

  • 4. 
    Data quality does not refer to
    • A. 

      Volume

    • B. 

      Accuracy

    • C. 

      Consistency

    • D. 

      Integrity

  • 5. 
    Which is not a data quality tool?
    • A. 

      Quality stage

    • B. 

      Trillium

    • C. 

      Data Stage

    • D. 

      All the options

  • 6. 
    Rule repository contains Databases or Flat Files
    • A. 

      True

    • B. 

      False

  • 7. 
    Which are the following is not an IBM product?
    • A. 

      Meta stage

    • B. 

      Quality Stage

    • C. 

      Profile Stage

    • D. 

      Analysis stage

  • 8. 
    Data quality audit provides traceability between original and corrected values.
    • A. 

      True

    • B. 

      False

  • 9. 
    Bad quality data affects concurrency and performance.
    • A. 

      True

    • B. 

      False

  • 10. 
    Tracing involves audit trails between deleted and surviving customers
    • A. 

      True

    • B. 

      False

  • 11. 
    Survivorship is a concept used in 
    • A. 

      Data de-duplication

    • B. 

      Cleansing

    • C. 

      Enrichment

    • D. 

      None

  • 12. 
    Data masking and mask pattern analysis are used in substituting string patterns
    • A. 

      True

    • B. 

      False

  • 13. 
    Customer merging is matching the best attribute into the surviving records from duplicate records
    • A. 

      True

    • B. 

      False

  • 14. 
    Customer matching is done with Fuzzy and intelligent logic.
    • A. 

      True

    • B. 

      False

  • 15. 
    Data quality (MDM) involves avoiding overheads while preparing the DW.
    • A. 

      True

    • B. 

      False

  • 16. 
    During which of the operations data is not modified
    • A. 

      Data profiling

    • B. 

      Data cleansing

    • C. 

      Data enrichment

    • D. 

      None

  • 17. 
    MDM is maintained at organizational level
    • A. 

      True

    • B. 

      False

  • 18. 
    During the de-duplication process
    • A. 

      Delete the original values since they consume space

    • B. 

      Keep the original values in trail tables

    • C. 

      Do not disturb the original values and place the new values in new tables

    • D. 

      None

  • 19. 
    Data cleansing and standardization will be taken care by
    • A. 

      Data Profiling Tools

    • B. 

      Data Quality Tools

    • C. 

      Metadata Tools

    • D. 

      ETL Tool

  • 20. 
    What is the language used in a data quality tool?
    • A. 

      C

    • B. 

      JAVA

    • C. 

      C#

    • D. 

      COBOL

  • 21. 
    Household matching is for 
    • A. 

      Business

    • B. 

      Product

    • C. 

      Customer

    • D. 

      None of the above.

  • 22. 
    Trillium server process requires 
    • A. 

      Input Structure(DLL file)

    • B. 

      Output structure (DLL file)

    • C. 

      Parameter file (PAR file)

  • 23. 
    The rules of cleansing are embedded in Trillium’s 
    • A. 

      Parameter file (PAR).

    • B. 

      Output structure (DLL file)

    • C. 

      Input structure (DLL file)

  • 24. 
    Trillium source 
    • A. 

      Flat files, fixed width

    • B. 

      Flat file ,comma separated

    • C. 

      ODBC connection

    • D. 

      All

  • 25. 
    Basic Functionalities of Trillium
    • A. 

      Data Profiling

    • B. 

      Data Quality

    • C. 

      Data Enrichment

    • D. 

      Data Volume