Anomalies in database
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This document discusses database anomalies that can occur when data is stored in a single, unnormalized table. It provides examples of insert, delete, and update anomalies and how normalization helps address these issues. The document also demonstrates how to model relationships between entities as relations and add foreign keys to represent those relationships without anomalies.
Anomalies in database
- 2. Disclaimer: This presentation is prepared by trainees of baabtra as a part of mentoring program. This is not official document of baabtra –Mentoring Partner Baabtra-Mentoring Partner is the mentoring division of baabte System Technologies Pvt . Ltd
- 3. Anomalies in Database Name @abhishekmenon121989@gmail .com www.facebook.com/ Abhishek H menon twitter.com/Abhishek H Menon in.linkedin.com/in/Abhishek H menon
- 4. Anomaly Normalization is a technique for producing relational schema with the following properties. • no information redundancy. • no anomalies. so we are clear when the process of reducing the anomaly comes into action.
- 5. What is an Anomaly? • Definition – Problems that can occur in poorly planned, un- normalized databases where all the data is stored in one table (a flat-file database).
- 6. Types of Anomalies • Insert • Delete • Update
- 7. Insert Anomaly • An Insert Anomaly occurs when certain attributes cannot be inserted into the database without the presence of other attributes.
- 8. Insert Anomaly Course _no Tutor Room Room_size En_limit 353 Smith A532 45 40 351 Smith C320 100 60 355 Clark H940 400 300 456 Turner H940 400 45 e.g. we have built a new room (e.g. B123) but it has not yet been timetabled for any courses or members of staff.
- 9. Delete Anomaly • A Delete Anomaly exists when certain attributes are lost because of the deletion of other attributes.
- 10. Delete Anomaly Course_no Tutor Room Room_size En_limit 353 Smith A532 45 40 351 Smith C320 100 60 355 Clark H940 400 300 456 Turner H940 400 45 e.g. if we remove the entity, course_no:351 from the above table, the details of room C320 get deleted. Which implies the corresponding course will also get deleted.
- 11. Update Anomaly • An Update Anomaly exists when one or more instances of duplicated data is updated, but not all.
- 12. Update Anomaly Course_no Tutor Room Room_size En_limit 353 Smith A532 45 40 351 Smith C320 100 60 355 Clark H940 400 300 456 Turner H940 400 45 e.g. Room H940 has been improved, it is now of RSize = 500. For updating a single entity, we have to update all other columns where room=H940.
- 13. A conceptual model • Consider the following ‘simple’ conceptual data model: Staff( Staff-id, Name,address, scale_point, Rate_of_pay, DOB..) Student(Enroll-no, Name, Address, Olevelpoints..) Course(Course-code, Name, Duration..) Course StudentStaff M M1N
- 14. The ‘Translation’ process • Entities become relations. • Attributes become attributes. • Entity identifier (s) become primary key(s) • Relationships are represented by additional foreign keys attributes in those relation that are at the ‘M’ end of the 1:M relationship.
- 15. The ‘Staff’ and ‘Student’ relations • Staff(Staff-id, Name , Address, Rate-of-pay, DOB) • Student(Enrol-no, Name, Address, Olevelpoints, Tutor); NB: Foreign Key Tutor references Staff.Staff_id Staff_id Name Address Scale point Rate_of_pay DOB Enrol-no Name Address Olevelpoints Tutor
- 16. The ‘Staff’ & ‘Course’ relations • Staff • Course NB: according to the conceptual model specified, both the above entities have M:M relationships at the end. We must create an artificial link in between these two entities. Staff_id Name Address Scalepoint Rate_of_pay DOB Course-code Name Duration
- 17. The ‘Staff’, ‘Course’ and ‘Team’ relations • Staff • Team • Course Staff_id Name Address Scalepoint Rate_of_pay DOB Course_code Staff_id Course_code Name Duration
- 18. The ‘Staff’, ‘Course’ and ‘Team’ relations • In our new relation ‘Team’: – Primary key is the combination of Course_code and Staff_id. – Foreign key Course_code references Course.Course_code. – Foreign key Staff_id references Staff.Staff_id.
- 19. For 3 entities 4 relations • Student • Staff • Team • Course But these tables are not free from the above anomalies! Enrol_no Name Address Olevelpoints Tutor Staff_id Name Address Scalepoint RateofPay DOB Course_code Staff_id Course_code Name Duration
- 20. Checking for anomalies • every tuple unique? • no hidden meaning from location? • data cells atomic? • For relations with single_attribute keys: – every attribute depends upon the primary key • For relations with composite keys: – Every attribute depends upon the whole key(the components of this key are prime attributes?)
- 21. Relation fails • Especially when we check dependency between various attributes in a relationship. • So we must split that relation into two relations. • And we should create a foreign key in the new table which references the primary key in the old table.
- 22. Problem arises • The attribute ‘Rate_of_pay’ does not depends on the ‘Staff_id’ but on ‘Scalepoint’ in the relation Staff. • So the next step will be splitting the relation Staff into relation Staff and relation Pay. Staff Pay Where in new relation Pay; Combination of Scalepoint and rate_of_pay is taken as primary key. Foreign key Scalepoint references Staff.Scalepoint. Staff_id Name Address Scalepoint DOB Scalepoint Rate_of_Pay
- 23. For 3 entities 5 relations • Student • Staff • Team • Course • Pay Enrol_no Name Address Olevelpoints Tutor Staff_id Name Address Scalepoint DOB Course_code Staff_id Course_code Name Duration Scalepoint Rate_of_pay
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