What consequences can result from violating data normalization in a database?

Data normalization violations in a database can lead to the following problems:

• Data Redundancy: Repetition of the same data in multiple places. This increases the volume of stored information and creates a risk of data inconsistency during updates.
• Update Anomalies: The inability to correctly update data without violating its integrity. If data is duplicated, an update in one place may leave outdated information elsewhere.
• Insertion Anomalies: The inability to add new information to the database until related information exists. For example, it is impossible to add data about a new product without data about the supplier, even if the supplier information is not yet available.
• Deletion Anomalies: Deleting some information results in the deletion of related but necessary information. For example, deleting data about an employee may lead to deleting data about the department where they worked if they are stored in a single non-normalized table.
• Data Integrity Violations: Due to redundancy and anomalies, data can become contradictory and unreliable.
• Increased Query Complexity: Retrieving complete and consistent information may require complex table joins (JOIN), which degrades performance.
• Schema Modification Complexity: Making changes to the database structure becomes more difficult and risky.