Download A Developer's Guide to Data Modeling for SQL Server: by Eric Johnson PDF

By Eric Johnson

Potent facts modeling is key to making sure that your databases will practice good, scale good, and evolve to satisfy altering requisites. even if, in case you are modeling databases to run on Microsoft SQL Server 2008 or 2005, theoretical or platform-agnostic info modeling wisdom is not adequate: versions that do not mirror SQL Server's designated real-world strengths and weaknesses frequently result in disastrous functionality.

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Additional info for A Developer's Guide to Data Modeling for SQL Server: Covering SQL Server 2005 and 2008

Example text

Two character large object (CLOB) data types handle this information: text and ntext. These two data types are designed to handle large amounts of character data in a single field. Again, as with the other character data types, the n prefix indicates whether or not the data is being stored in the Unicode format. Choose these data types when you will have very large amounts of alphanumeric text stored as a single attribute in an entity. Dates and Times Nearly every data model in existence requires that some entities have attributes that are related to dates and times.

2 The Schools entity are stored in the Schools entity. Although this approach consolidates all information in a single entity, it is not the most flexible solution. Whenever either a school or a dean is updated, the record must be retrieved and updated. Additionally, having a school with no dean (or a dean with no school) creates a half-empty record. Finally, it creates data retrieval problems. What if you want to write a report to return information about deans? You would have to retrieve school data as well.

That brings me to the Question table, which, as the name suggests, stored the questions for the exams. This table also stored the possible answers the students could choose. 5, this table had problems. info 12 Chapter 1 Data Modeling Overview Let’s take a look at what makes this a bad design and how that affects data retrieval. The first four columns are OK; they store information about the question, such as the test where it appears and the question’s category. The problems start to become obvious in the next five columns.

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