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Data Management Fundamentals Questions 96–100 (page: 21)

Updated On: 10-Feb-2026

Discovering and documenting metadata about physical data assets provides:

  1. Scoping boundaries of the data dictionary
  2. An estimation of balance sheet value of enterprise data
  3. Effective project scope management
  4. Insights into the temporal data quality
  5. Information on how data is transformed as it moves between systems

Answer(s): E



Data Fabric is:

  1. A form of data lake that automates data acquisition and initial data quality processing
  2. Just another data warehouse with no distinguishing features
  3. A way of sewing together different data concepts into a single data warehouse
  4. A superior star schema strategy
  5. A metadata repository

Answer(s): A



An application that attempts to predict future outcomes through probability estimates is called:

  1. Just-in-time reporting
  2. Dimensional analytics
  3. Predictive analytics
  4. Descriptive analytics
  5. Reactive analytics

Answer(s): C



Which of the following is the best example of the data quality dimension of 'consistency'?

  1. All the records in the CRM have been accounted for in the data warehouse
  2. The source data for the end of month report arrived 1 week late
  3. The phone numbers in the customer file do not adhere to the standard format
  4. The revenue data in the dataset is always $100 out
  5. The customer file has 50% duplicated entries

Answer(s): C



Sentiment analysis of call centre voice files is performed by text analysis and stored in a relational database.
Which of the following is true?

  1. Structured and unstructured data are the same thing
  2. They are both structured data
  3. They are both unstructured data
  4. The voice files are structured data and the sentiment analysis is unstructured data
  5. The voice files are unstructured data and the sentiment analysis is structured data

Answer(s): E

Explanation:

The voice files contain raw audio data, which is typically considered unstructured data since it does not fit into a predefined model or format. On the other hand, sentiment analysis involves processing and extracting structured information (e.g., sentiment score, categories) from the unstructured voice data, which can be stored in a structured format such as a relational database.



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