Normalization Phase Four in Database Management Systems
To eliminate redundancy and ensure a cleaner, more efficient database design, it's essential to decompose tables that violate the Fourth Normal Form (4NF). This process aims to remove any non-trivial multivalued dependencies, leading to a more logical and future-proof data model.
Steps to Decompose a Database Table
Follow these specific steps to decompose a database table and achieve 4NF:
- Ensure the relation is in Boyce-Codd Normal Form (BCNF): First, confirm that the table already satisfies BCNF. This means all determinants in functional dependencies are candidate keys, so no partial or transitive dependencies exist.
- Identify multivalued dependencies (MVDs): Find any non-trivial MVDs in the relation. A multivalued dependency (X \twoheadrightarrow Y) means that for each value of (X), there is a set of multiple independent (Y) values. If these MVDs are present and do not stem from a candidate key, the table violates 4NF.
- Decompose the table to remove MVDs: For each non-trivial multivalued dependency (X \twoheadrightarrow Y), split the original relation into two relations:
- One relation contains the attributes (X) and (Y).
- The other relation contains (X) and the remaining attributes not in (Y).
This decomposition isolates the independent multiple sets of data into separate tables, eliminating redundancy caused by multivalued dependencies.
- Verify the decomposed tables meet 4NF criteria: After decomposition:
- Each table should be in BCNF.
- No relation should contain non-trivial multivalued dependencies unless they involve a candidate key.
This ensures every table abides by 4NF, preventing redundant pairings and anomalies like insertion, deletion, or update anomalies.
- Check for lossless join: Ensure that the decomposition is lossless, meaning the original table can be reconstructed by joining the decomposed tables on the common key(s), preserving all original information without spurious tuples.
Example:
Consider a table containing data about students, courses, and textbooks. If a student can take multiple courses and use multiple textbooks independently, split it into:
- A Student-Course relation (student ID, course ID)
- A Student-Textbook relation (student ID, textbook ID)
This removes the multivalued dependency and achieves 4NF.
This decomposition improves clarity, reduces redundancy, and prevents anomalies, leading to a cleaner, more efficient database design.
References
The structure of the decomposed tables meets the Boyce-Codd Normal Form (BCNF) and the Fourth Normal Form (4NF). A table with a multivalued dependency violates the normalization standard of the Fourth Normal Form (4NF) because it creates unnecessary redundancies and can contribute to inconsistent data. Decomposition ensures the tables are in BCNF and 4NF, with no partial, transitive or multivalued dependencies.
An example of multivalued dependencies is a course having multiple instructors and multiple textbook authors, where instructors and authors are independent of each other. Decomposing tables to eliminate multivalued dependencies is about making the data model more logical, efficient, and future-proof. The Fourth Normal Form (4NF) is a level of database normalization where there are no non-trivial multivalued dependencies other than a candidate key. A multivalued dependency occurs when one attribute determines multiple independent values of another attribute in a relation. In a non-4NF table, unrelated attribute combinations are repeated unnecessarily, leading to a cartesian product effect. The table should have B and C independent for A ->> B multivalued dependency. Each relation in the decomposed tables represents one fact, reducing logical complexity.
- Integrating the concept of a 'trie' in database design can facilitate the indexing and fast retrieval of medical-conditions for a 'medical-conditions' table, optimizing database performance and efficiency.
- The 'technology' of integrating machine learning algorithms with decomposed database structures can help in automatic detection of patterns and tendencies related to medical-conditions, aiding in the prediction of possible future medical-conditions and improving the overall quality of healthcare.
