Data Subsetting — Learn free

Self-check

Questions 1–10 of 10

1. What is data subsetting?
Question 1A. Encrypting a portion of a database for secure transferB. Taking a small piece of data, with referential integrity in place, for some activityC. Deleting old records to reduce database sizeD. Replacing sensitive values with fake onesE. Copying an entire database to a test server
2. Which property must a data subset preserve?
Question 2A. Encryption at restB. Column-level maskingC. Referential integrityD. Real-time refreshE. Cross-border storage
3. In the data subsetting example for a data science model, which users' data is extracted?
Question 3A. All users in the databaseB. Users aged between 25 and 35 from a particular location with certain buying or spending patternsC. Users who have opted out of marketingD. Users with the highest lifetime spendE. Users registered in the last month
4. Data subsetting should not be confused with which other practice?
Question 4A. Data maskingB. Data warehousingC. Data scrapingD. Data federationE. Data encoding
5. Is data masking still required after a data subset has been created?
Question 5A. No, because the subset is small enough to be safeB. No, because subsetting removes sensitive columnsC. Yes, from a security point of viewD. Only if the subset leaves the countryE. Only if the subset is larger than the original
6. What must one understand first before conducting a data subsetting exercise?
Question 6A. The cost of cloud storageB. The functional requirements of the use caseC. The encryption standard used by the databaseD. The number of database administratorsE. The BI tool the business prefers
7. Besides the use-case requirements, what else must be understood before subsetting data?
Question 7A. What data is in the database as a wholeB. Which vendor hosts the databaseC. How many users will view the subsetD. The network bandwidth availableE. The age of the database software
8. What is the consequence of wrong or partial data subsetting?
Question 8A. Faster model trainingB. Wrong data model results and damaged trust in data by decision-makersC. Reduced need for data maskingD. Automatic correction by the data science teamE. Lower storage costs
9. In the data subsetting example, who receives the extracted data set and for what purpose?
Question 9A. The finance team, to produce quarterly reportsB. The security team, to audit accessC. The data science development team, to build and train their modelsD. The regulator, to verify complianceE. The marketing team, to send emails
10. Which statement about the difficulty of data subsetting is correct?
Question 10A. It is trivial once the database is encryptedB. It requires no knowledge of the use caseC. It can be done by simply copying a random sample of rowsD. Although the idea is simple, conducting the exercise is not as simple as it soundsE. It is only difficult for NoSQL databases