Normalization is a key concept in database management systems (DBMS) aimed at reducing redundancy in tables. Redundancy can manifest at both the row level and the column level. Row level duplicacy occurs when identical rows exist in a table. For example, in a student table with student ID, name, and age, if two rows have the same data, this indicates row level duplicacy. To eliminate this, a primary key can be established, ensuring that each row is unique and contains no null values. For instance, setting the student ID as the primary key prevents duplicate entries for that field. Column level duplicacy can also occur, where different rows share identical values in certain columns. Although a primary key can eliminate row level duplicacy, it does not prevent repeated values in other columns. In an example with course-related data, multiple rows may have the same course ID or faculty name, indicating column level duplicacy. While the normalization process effectively addresses row level duplicacy through the implementation of primary keys, managing column level duplicacy often requires further structural adjustments in the database design.