Please read the Introductory Post before continue reading interview question and answers.
Relational Data Base Management Systems (RDBMS) are database management systems that maintain data records and indices in tables. Relationships may be created and maintained across and among the data and tables. In a relational database, relationships between data items are expressed by means of tables. Interdependencies among these tables are expressed by data values rather than by pointers. This allows a high degree of data independence. An RDBMS has the capability to recombine the data items from different files, providing powerful tools for data usage. (Read more here)
Relational tables have the following six properties:
Database normalization is a data design and organization process applied to data structures based on rules that help building relational databases. In relational database design, the process of organizing data to minimize redundancy is called normalization. Normalization usually involves dividing a database into two or more tables and defining relationships between the tables. The objective is to isolate data so that additions, deletions, and modifications of a field can be made in just one table and then propagated through the rest of the database via the defined relationships.
De-normalization is the process of attempting to optimize the performance of a database by adding redundant data. It is sometimes necessary because current DBMSs implement the relational model poorly. A true relational DBMS would allow for a fully normalized database at the logical level, while providing physical storage of data that is tuned for high performance. De-normalization is a technique to move from higher to lower normal forms of database modeling in order to speed up database access.
ACID (an acronym for Atomicity Consistency Isolation Durability) is a concept that Database Professionals generally look for while evaluating databases and application architectures. For a reliable database, all this four attributes should be achieved.
Atomicity is an all-or-none proposition.
Consistency guarantees that a transaction never leaves your database in a half-finished state.
Isolation keeps transactions separated from each other until they are finished.
Durability guarantees that the database will keep track of pending changes in such a way that the server can recover from an abnormal termination. (Read more here)
1NF: Eliminate Repeating Groups
Make a separate table for each set of related attributes, and give each table a primary key. Each field contains at most one value from its attribute domain.
2NF: Eliminate Redundant Data
If an attribute depends on only part of a multi-valued key, then remove it to a separate table.
3NF: Eliminate Columns Not Dependent On Key
If attributes do not contribute to a description of the key, then remove them to a separate table. All attributes must be directly dependent on the primary key. (Read more here)
BCNF: Boyce-Codd Normal Form
If there are non-trivial dependencies between candidate key attributes, then separate them out into distinct tables.
4NF: Isolate Independent Multiple Relationships
No table may contain two or more 1:n or n:m relationships that are not directly related.
5NF: Isolate Semantically Related Multiple Relationships
There may be practical constrains on information that justify separating logically related many-to-many relationships.
ONF: Optimal Normal Form
A model limited to only simple (elemental) facts, as expressed in Object Role Model notation.
DKNF: Domain-Key Normal Form
A model free from all modification anomalies is said to be in DKNF.
Remember, these normalization guidelines are cumulative. For a database to be in 3NF, it must first fulfill all the criteria of a 2NF and 1NF database.
Reference: Pinal Dave (http://blog.SQLAuthority.com)