Archive for April, 2007

Benefits of Normalization Effectively minimizing redundancy is another (Web hosting compare)

Monday, April 30th, 2007

Benefits of Normalization Effectively minimizing redundancy is another way of describing removal of duplication. The effect of removing duplication is as follows: . Physical space needed to store data is reduced. . Data becomes better organized. . Normalization allows changes to small amounts of data (namely single records) to be made to one table at once. In other words, a single table record is updated when a specific item is added, changed, or removed from the database. You don t have to search through an entire database to change a single field value in a single record, just the table. 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. Representing Relationships in an ERD Tables can have various types of relationships between them. The different types of inter-table relationships that can be formed between different tables can be best described as displayed in Entity Relationship Diagrams (ERDs). 49 Database Modeling Building Blocks
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Web site template - . NOT NULL This is the simplest of field

Monday, April 30th, 2007

and numbers. Storage issues can become problematic. (Web hosting domain) Relational

Monday, April 30th, 2007

Web hosting mysql - Figure 3-9: Dates with timestamps and dates without

Monday, April 30th, 2007

. Floating points A floating-point (Web design) number is just as

Sunday, April 29th, 2007

. Numbers Numeric datatypes are often the most numerous (Best web design)

Sunday, April 29th, 2007

Figure 3-6: Fixed-length strings and variable-length strings. . (Crystaltech web hosting)

Sunday, April 29th, 2007

Web hosting contract - Whereas fields apply structure to records, datatypes apply

Sunday, April 29th, 2007

Figure 3-5: The vertical structure of a table (Make a web site)

Saturday, April 28th, 2007

Unlimited web hosting - Figure 3 -4: Records repeat table field structure.

Saturday, April 28th, 2007