17. Which data manipulation activities will cause integrity issues?
Answer: D
Calculating the difference between two date fields that are in different formats can cause integrity issues.
When calculating the difference between date fields in different formats, the inconsistency in formatting can lead to incorrect calculations and misinterpretation of data, thus causing integrity issues.
A) Adding new columns to a table for quarter and year from the date field
This action does not inherently cause integrity issues, as it simply involves extracting information from an existing date field to create additional columns. As long as the extraction is done correctly, the integrity of the data remains intact.
B) Converting different currencies to a single currency based on standard conversion ratios
Converting currencies using standard conversion ratios is a standard data manipulation practice that does not typically introduce integrity issues, provided the conversion rates are accurate and consistently applied. This process enhances data coherence rather than compromising integrity.
C) Combining information from multiple tables into a single table based on a primary key
Combining data from multiple tables using a primary key is a fundamental database operation that maintains data integrity, assuming the primary keys are correctly defined and consistent across the tables. This operation is designed to preserve relationships and integrity within the dataset.
D) Calculating the difference between two date fields that are in different formats
This option is correct because different date formats may lead to incorrect data interpretation and calculations. For example, if one date is in MM/DD/YYYY format and another in DD/MM/YYYY, subtracting them without proper conversion can yield erroneous results, compromising the data's integrity.
Conclusion
In summary, option D is the only choice that directly leads to integrity issues due to the potential for miscalculation stemming from inconsistent date formats. In contrast, options A, B, and C represent data manipulation activities that are standard practices which, when executed properly, maintain or enhance data integrity.