Potential Normalization Hazards

There are potential problems in taking this redundancy minimization process too far. Some detailed aspects of the positive effects of normalization mentioned previously can have negative side effects, and sometimes even backfire, depending on the application focus of the database. Performance is always a problem with too much granularity caused by over-application of normalization. Very demanding concurrency
OLTP databases can be very adversely affected by too much granularity. Data warehouses often require non-technical end-user access and over-granularity tends to make table structure more technically oriented to the point of being impossible to interpret by end-users.

Keep the following in mind:

- Physical space is not nearly as big a concern as it used to be, because disk space is one of the cheapest cost factors to consider (unless, of course, when dealing with a truly huge data warehouse).

- Too much minimization of redundancy implies too much granularity and too many tables. Too many tables can lead to extremely huge SQL join queries. The more tables in a SQL join query, the slower queries execute. Performance can be so drastically affected as to make applications completely useless.

- Better organization of data with extreme amounts of redundancy minimization can actually result in more complexity, particularly if end-users are exposed to database model structure.

The deeper the level of normalization, the more mathematical the model becomes, making the model "techie-friendly" and thus very "user-unfriendly." Who is accessing the database, end-users or OLTP applications?

Tables are connected to each other with relationships. Examine what a relationship is and how it can be represented.