medivieal history
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Questions and Answers

What is the primary challenge in effectively processing large datasets?

  • Data normalization and standardization
  • Handling missing or inconsistent data (correct)
  • Ensuring data is up to date
  • Finding and removing duplicates
  • Which method is least effective in improving data quality?

  • Conducting regular data audits
  • Training staff on data entry techniques
  • Ignoring errors found during processing (correct)
  • Implementing automated validation checks
  • Which of the following techniques is most used for data cleansing?

  • Data profiling
  • Data enrichment
  • Data wrangling (correct)
  • Data visualization
  • Which factor is critical for ensuring data privacy?

    <p>Data encryption methods</p> Signup and view all the answers

    What outcome is most likely from poor data governance?

    <p>Higher risk of data breaches</p> Signup and view all the answers

    What element is commonly overlooked when managing large datasets?

    <p>Data ownership clarity</p> Signup and view all the answers

    Which of the following is a significant risk associated with handling sensitive data?

    <p>Data breaches</p> Signup and view all the answers

    What factor often contributes to the failure of data-driven decision making?

    <p>Poor data quality</p> Signup and view all the answers

    Which aspect of data governance is typically prioritized to enhance compliance?

    <p>Data retention policies</p> Signup and view all the answers

    What element is essential for successful data integration from various sources?

    <p>Unique data identifiers</p> Signup and view all the answers

    Study Notes

    Title: History of Medieval India (800-1700)

    • Author: Satish Chandra
    • Publisher: Orient BlackSwan
    • Book covers the history of medieval India from 800 to 1700 AD

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    Description

    This quiz explores key challenges and techniques in data management, focusing on data quality, governance, and privacy. Test your understanding of the most effective methods for data cleansing and the potential consequences of poor data governance.

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