Cartesian Data — Learn free

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Questions 1–10 of 10

1. What is Cartesian Data about?
Question 1A. Writing a query on tables with a 'Many to Many' relationshipB. Storing coordinates in a geographic tableC. Encrypting data in transitD. Partitioning a table by dateE. Normalising a table to 3NF
2. What should a data modeller introduce when two tables have a 'Many to Many' relationship?
Question 2A. A second primary key on each tableB. An intermediary table with unique records that has 'One to Many' relationships with both tablesC. A UNION ALL between the two tablesD. A trigger that deletes duplicatesE. A full outer join
3. Why does joining the Sales table directly to the Target table on Employee ID produce Cartesian data?
Question 3A. Because Employee ID is a text columnB. Because both Sales and Target tables can contain more than one row per Employee IDC. Because the Target table is emptyD. Because Sales has no Employee IDE. Because the join uses an index
4. Which department is said to get nightmares from Cartesian data, seeing USD 200k when they know the total is USD 100k?
Question 4A. MarketingB. Human ResourcesC. FinanceD. LegalE. Procurement
5. Even with an intermediary table in place, what can still cause Cartesian data?
Question 5A. A wrongly written query, known as a Chasm TrapB. Adding a primary keyC. Using UNION ALLD. Running the query at nightE. Having too few rows
6. In the John example, how many rows are produced when Employee, Target and Sales are joined in one query?
Question 6A. 2B. 10C. 12D. 20E. 100
7. What is the correct row count after resolving the John example with UNION ALL?
Question 7A. 2 rowsB. 10 rowsC. 12 rowsD. 20 rowsE. 24 rows
8. In the department and salary example, how many rows result from joining Dept (2 rows for an employee) and Sal (12 monthly rows) on Employee ID?
Question 8A. 12 rows with the correct salaryB. 14 rows with the correct salaryC. 24 rows with the salary doubledD. 2 rows with the salary halvedE. 1 row with the correct salary
9. How should the Dept and Sal tables be joined to avoid Cartesian data?
Question 9A. Directly on Employee IDB. Each should first join the Employee table, which always has a unique row per employeeC. On the month columnD. Using a CROSS JOINE. They should never be queried
10. Which of the following is NOT listed as a cause or symptom of Cartesian data?
Question 10A. Joining two tables that both have duplicates on the join columnB. Writing one query across tables with Many to Many relationshipsC. A Chasm Trap in a badly written queryD. Totals appearing doubled in Finance reportsE. Using an intermediary table with unique records