Granularity — Learn free

Self-check

Questions 1–10 of 10

1. What does the granularity of data mean?
Question 1A. The physical size of the database filesB. The levels of data breakdownC. The number of users with accessD. The speed of query executionE. The number of tables in a schema
2. What do people generally, but mistakenly, think granularity is?
Question 2A. Having a primary key on every tableB. Having all relevant details about an entity, without asking what level of detailC. Storing data in the CloudD. Normalising to Third Normal FormE. Keeping only summary data
3. Which of these is an example of breaking Name down to a lower level of granularity?
Question 3A. Storing Name with Email and Contact NumberB. Storing Name in upper caseC. Splitting Name into First Name, Middle Name and Last NameD. Storing Name as a numberE. Removing Name from the table
4. How low should granularity go in OLTP systems compared with OLAP systems?
Question 4A. OLTP as low as possible; OLAP depends on the business use caseB. OLAP as low as possible; OLTP depends on the business use caseC. Both must always be at the highest summary levelD. Both must always be at the lowest levelE. Granularity does not apply to OLTP
5. Why does lower granularity matter for Data Wrangling, Data Mining and Data Science?
Question 5A. Because it reduces the number of rowsB. Because regulators require itC. Because it eliminates the need for cleaningD. Because these disciplines use raw data, and the lower the granularity the better the model result for decision supportE. Because it speeds up backups
6. What should be the first step towards creating a data model, according to the discussion of granularity?
Question 6A. Choosing a database vendorB. Designing the dashboardsC. Understanding the level of granularity the system or business use case expectsD. Writing the ETL jobsE. Assigning data stewards
7. How does choosing a Date rather than a DateTime data type affect granularity?
Question 7A. It has no effect on granularityB. It removes the need for a time dimensionC. It doubles the number of rowsD. It changes the level of granularityE. It makes the column a primary key
8. What happens to the number of rows as the granularity level gets lower?
Question 8A. The number of rows decreasesB. The number of rows stays the sameC. Rows are merged into summariesD. Rows are replaced by columnsE. The number of rows increases, allowing more drilling and slicing/dicing
9. Which of the following is NOT listed among the activities whose results depend on the level of granularity in the data model?
Question 9A. Master Data ManagementB. Data LineageC. Data Classification and ClusteringD. Business Intelligence DashboardsE. Network firewall configuration
10. Which related topic are readers told not to miss after Granularity?
Question 10A. CardinalityB. Zero TrustC. Lambda ArchitectureD. Data CatalogE. SaaS