Proper physical database design is one of the most important steps a database designer can take to impact performance database. When physically designing the database, it is important for the designer to understand what type of data will be included and how that data will be used. To better understand why this is important, let's first break down some of the basic elements that are important when designing the physical database. One of the most fundamental metrics that must be considered and planned concerns the smallest units of the database, the fields. Fields are derived from simple attributes defined in the logical data model. A few decisions need to be made regarding each of these individual areas. First of all, what type of data will be stored there? The data type assigned to each field must be capable of accurately representing all possible valid values, while limiting invalid values ​​as much as possible. Careful consideration should be given to any manipulations that will be performed on the data, as some data types allow these manipulations much more easily than others. When considering data manipulations, it's important to keep simple things like addition in mind. If you are looking for the sum of the data field values, the data type that worked for the fields may not be large enough to support the resulting sum. Related to the actual data type chosen, a number of other checks can be attached to fields to better ensure data integrity. One of these controls is simply the default value that the field should take, unless it is assigned another value. If done correctly, setting a default can be very beneficial as it could...... middle of paper ......grit can be implemented and the performance impact can be minimized. When looking at some of the more advanced design methods mentioned, it is essential to understand data and how it is used. It also doesn't hurt to have a few tools to help you along the way. Works Cited Hoffer, J. (2011). Modern database management. Upper Saddle River, NJ: Prentice Hall. Lightstone, S. (2007). Physical Database Design: The Database Professional's Guide to Leveraging Indexes, Views, Storage, and More Amsterdam Boston: Morgan Kaufmann/Elsevier. Konig, AC; Nabar, S.U. (2006). Proceedings ICDE '06: 22nd International Conference on Data Engineering: April 3-7, 2006, Atlanta, Georgia / Editors, Roger S. Barga, Xiofang Zhou. Los Alamitos, CA: IEEE Computer Society. Retrieved from: http://ieeexplore.ieee.org.portal.lib.fit.edu/stamp/stamp.jsp?tp=&arnumber=1617405