| Goal | This query identifies base table columns designated for storing codes (e.g., vin and isbn codes) that lack appropriate length constraints reflecting real-world data requirements. It operates on a heuristic basis, targeting columns whose identifiers imply code data (e.g., names containing "isbn" or "vin") but whose definitions fail to account for standard maximum lengths. This includes both insufficient allocation (truncation risk) and unbounded allocation (data quality risk). Ensuring these fields are sized according to domain standards is crucial for data integrity and usability. |
|---|---|
| Type | Problem detection (Each row in the result could represent a flaw in the design) |
| Reliability | Medium (Medium number of false-positive results) |
| License | MIT (opens in new tab) |
| Data Source | INFORMATION_SCHEMA only |
| SQL Query |
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Collections
This query belongs to the following collections:
Find problems automatically
Queries, that results point to problems in the database. Each query in the collection produces an initial assessment. However, a human reviewer has the final say as to whether there is a problem or not .
| Name | Description |
|---|---|
| Find problems automatically | Queries, that results point to problems in the database. Each query in the collection produces an initial assessment. However, a human reviewer has the final say as to whether there is a problem or not . |
Categories
This query is classified under the following categories:
Field size
Queries of this category provide information about the maximum size of values that can be recorded in column fields
Result quality depends on names
Queries of this category use names (for instance, column names) to try to guess the meaning of a database object. Thus, the goodness of names determines the number of false positive and false negative results.
| Name | Description |
|---|---|
| Field size | Queries of this category provide information about the maximum size of values that can be recorded in column fields |
| Result quality depends on names | Queries of this category use names (for instance, column names) to try to guess the meaning of a database object. Thus, the goodness of names determines the number of false positive and false negative results. |