| Goal | This query identifies a semantic mismatch in data type selection for columns intended to store telephone numbers. It flags columns whose identifiers imply phone number content (e.g., names containing "phone", "mobile", "telef") but are defined with non-textual data types (e.g., INTEGER, NUMERIC, BIGINT). Telephone numbers are semantically strings, as they may contain leading zeros, international prefixes (+), and formatting characters (-, (), ext.), and are not subject to arithmetic operations. Storing them as numeric types leads to data loss (truncation of leading zeros) and formatting inflexibility. |
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| Notes | The query considers both column names in English and Estonian. |
| Type | Problem detection Each row in the result could represent a flaw in the design |
| Reliability | High Few or no false-positive results |
| License | MIT (opens in new tab) |
| Fixing Suggestion | Change the type of the column to VARCHAR(n) or TEXT. In the latter case add an additional constraint to the maximum value length permitted in the column. |
| Data Source | INFORMATION_SCHEMA only |
| SQL Query |
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Collections
This query belongs to the following collections:
Find problems about base tables
A selection of queries that return information about the data types, field sizes, default values as well as general structure of base tables. Contains all the types of queries - problem detection, software measure, and general overview
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 about base tables | A selection of queries that return information about the data types, field sizes, default values as well as general structure of base tables. Contains all the types of queries - problem detection, software measure, and general overview |
| 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:
Data types
Queries of this category provide information about the data types and their usage.
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 |
|---|---|
| Data types | Queries of this category provide information about the data types and their usage. |
| 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. |