"Denormalization Functionality" Please respond to the following:
Having an adequate data model to serve specific business needs of an organization is important. Evaluate the need for denormalization within an organization. Provide at least three examples that prove denormalization is useful to data consumers.
Using a data-modeling checklist can help database developers design efficient data repositories. Suggest at least two possible scenarios that could take place if one of the steps in the data-modeling checklist (table 6.7 in Chapter 6 of the textbook) is missed.
Classmate:
Having an adequate data model to serve specific business needs of an organization is important. Evaluate the need for denormalization within an organization. Provide at least three examples that prove denormalization is useful to data consumers.
The first reason to use denormalization is to improve query performance in the database. Denormalization increases the read performance of the database while sacrificing some write performance of the database. An organization may have more people searching a database, such as a library card catalog, but not doing as many writes to the database.
Another use for denormalization is to improve reporting on the database. Temporarily tables can hold denormalized data to run a specific report and can be deleted when no longer needed for the report. Also by having a temporary table you do not have to query all of the tables within the database and this helps speed up the report.
A final use for denormalization is to maintain the history of the database. You can use a table to track changes of the database and know when a change was made, who made the change, and what was changed. This can help avoid redundant data within the database as well.
Using a data-modeling checklist can help database developers design efficient data repositories. Suggest at least two possible scenarios that could take place if one of the steps in the data-modeling checklist (table 6.7 in Chapter 6 of the textbook) is missed.
One of the biggest one that stands out to me is the naming conventions of database. If you name is too short, too long, or has no meaningful name to the database it can be confusing when creating queries or designing web front-ends. Having good naming conventions helps keep future DBAs from having to figure out what a field or table name means or having to recreate tables and lose valuable resources.
The other piece of the checklist is clearly defined relationships. Not identifying proper relationships in the database can lead to poor performance and connectivity throughout the database. Having clearly defined relationships will also help when documenting and building the ER model of the database.