Information Systems for Business and Beyond (2019)

(2) Violation of data integrity Data integrity means consistency among the stored data. We use the above illustrative example to explain the concept of data integrity and how data integrity can be violated if the data system is flawed. You can find that Alex Wilson received a grade in MKT211; however, you can’t find Alex Wilson in the student roster. That is, the two rosters are not consistent. Suppose we have a data integrity control to enforce the rules, say, “no student can receive a grade unless she/he has registered and paid tuition”, then such a violation of data integrity can never happen. (3) Relying on human memory to store and to search needed data. The third common mistake in data resource management is the over use of human memory for data search. A human can remember what data are stored and where the data are stored, but can also make mistakes. If a piece of data is stored in an un-remembered place, it has actually been lost. As a result of relying on human memory to store and to search needed data, the entire data set eventually becomes disorganized. To avoid the above common flaws in data resource management, database technology must be applied. A database is an organized collection of related data. It is an organized collection, because in a database, all data is described and associated with other data. For the purposes of this text, we will only consider computerized databases. Though not good for replacing databases, spreadsheets can be ideal tools for analyzing the data stored in a database. A spreadsheet package can be connected to a specific table or query in a database and used to create charts or perform analysis on that data. Data Models and Relational Databases Information Systems for Business and Beyond (2019) pg. 70

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