Types Of Data Standards For A Business

996 Words4 Pages
1. What are the five data standards which an enterprise should establish? Who should participate in the development of these standards and why? Where are the standards kept? Answer: There are five types of data standards that must be established for a business. List of data standards: (i). Identifier (ii). Naming (iii). Definition (iv). Integrity rules (v). Usage rights Business supervisors, not IS supervisors, have the learning important to set these standards and therefore should actively participate in the standards-setting process. Frequently this participation happens through the part of information steward, who is a business chief in charge of the quality of data in a specific subject or…show more content…
Entities for book store: Address, Member, Books, Order, basket and Payment etc.. Relationship: An association between entities. Relationship for book store: Buy, goes to, dependence on and reduce total price. • We need Entity, relationship, attribute, entity type and record to develop the diagram. Entity Relationship diagram: 3. The textbook, in the section titled "Data Should Be Captured Once" on page 104, notes the example of the university that had student contact information stored in 12 different systems. Aside from the additional costs of maintaining such a system, what are some potential problems of such a system in between the university and students? Answer: If we not capture data from one database it’s too costly for management to maintain their student data. Here are the some potential problems between universities and students.  It is simply too costly for an organization to capture the same data multiple times and reconcile differences across applications.  Maintaining a student accounts and financial matters should be complicated.  Maintaining the student absence and attendance should be tough.  Handling a admission process is hard  Enrolling a new students and enabling online schedule. 4. What is the problem of "dirty data" and what are two general approaches to dealing with this problem? Answer: Problem of Dirty data: The cost of dirty data and poorly managed data are staggering. Poor data management costs global organizations
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