Data Anomalies — Learn free

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Questions 1–10 of 10

1. What are Data Anomalies?
Question 1A. Any kind of unusual behaviour which can degrade the quality of dataB. Statistical outliers in a numeric columnC. Errors in a BI dashboard layoutD. Unused indexes in a databaseE. Delays in a data pipeline
2. Which of the following is NOT one of the four types of Data Anomalies listed?
Question 2A. InsertionB. UpdateC. DeleteD. RedundancyE. Encryption
3. What is a Redundancy anomaly?
Question 3A. Being unable to enter quality data into a databaseB. Being able to update irrelevant dataC. Having duplicate records in a tableD. Deleting a whole department by deleting an employeeE. Losing a backup copy
4. Which two practices play a vital role in making sure data anomalies do not occur?
Question 4A. Data visualisation and heat mapsB. Data Normalisation and database constraintsC. Data surfing and ad hoc reportingD. Machine learning and deep learningE. Hub-and-spoke and point-to-point integration
5. In the de-normalised employee table example, a rule says department name cannot be NULL. What anomaly arises when a new employee has not yet been assigned a department?
Question 5A. A redundancy anomaly, because the employee is duplicatedB. A delete anomaly, because the department is removedC. An update anomaly, because the salary changesD. An insertion anomaly, because the employee record cannot be inserted and a report of all employees will be wrongE. No anomaly, because the rule is correct
6. In the de-normalised employee table example, what happens when the only employee in the HR department is deleted?
Question 6A. The HR department details are deleted as well, so analysis shows no HR department existsB. The salary column becomes NULLC. A duplicate HR department record is createdD. The employee is moved to the IT departmentE. The table is automatically normalised
7. In the employee table example, Adam has two departments, IT and Procurement. What update anomaly can occur when renaming IT to Tech Org?
Question 7A. Adam's salary is doubledB. Adam's record is deletedC. The update also changes Procurement to Tech Org, creating a data quality issueD. The update is rejected by the databaseE. A third department is added for Adam
8. Besides eliminating duplication of records, what other benefit is gained by normalising the employee table into separate department and salary tables?
Question 8A. Faster network speedB. Saving a lot of storageC. Better dashboard coloursD. Automatic data encryptionE. Removal of all database constraints
9. Which statement about data quality is made in the discussion of Data Anomalies?
Question 9A. Data quality is only about dirty dataB. Data quality applies only to reportsC. Data quality is unaffected by database designD. Data quality is measured only by row countsE. Data quality is not only about dirty data but also about being unable to insert, update and delete required data
10. How is an Update anomaly defined?
Question 10A. Being unable to enter quality data into a databaseB. Having duplicate records in a tableC. Being able to delete irrelevant dataD. Being unable to update relevant data, or being able to update irrelevant dataE. Being unable to create a new table