Podcast
Questions and Answers
Which of the following scenarios exemplifies row-level data duplication in a database table?
Which of the following scenarios exemplifies row-level data duplication in a database table?
- A product table where the 'color' attribute is repeated across different product entries.
- A sales table where multiple sales records have the same transaction date.
- An employee table with employees sharing the same department and job title.
- A student table containing identical rows for multiple students, including all attributes such as ID, name, and age. (correct)
How does defining a primary key in a database table address the issue of row-level data duplication?
How does defining a primary key in a database table address the issue of row-level data duplication?
- It enforces uniqueness and disallows null values, ensuring each row is uniquely identifiable. (correct)
- It allows null values in a column, thus accommodating different entries.
- It automatically creates an index that speeds up query performance.
- It compresses the data within a row, reducing storage space.
In a database context, what is an insertion anomaly?
In a database context, what is an insertion anomaly?
- The failure of a database system to start after a system crash.
- The difficulty in inserting a new record due to a full database.
- The inability to delete a record without affecting other related information.
- The inability to insert a new data record without also adding unrelated information. (correct)
Which database anomaly results in the unintentional loss of data due to the deletion of other data?
Which database anomaly results in the unintentional loss of data due to the deletion of other data?
What scenario exemplifies an update anomaly in a database?
What scenario exemplifies an update anomaly in a database?
How does normalization address column-level data duplication and associated anomalies in database design?
How does normalization address column-level data duplication and associated anomalies in database design?
Following normalization, what advantage is gained regarding the insertion of new data into a database?
Following normalization, what advantage is gained regarding the insertion of new data into a database?
After properly normalizing a database, what outcome is expected when deleting a student's record in a student table?
After properly normalizing a database, what outcome is expected when deleting a student's record in a student table?
How does normalization impact the process of updating a faculty member's salary in a database?
How does normalization impact the process of updating a faculty member's salary in a database?
Following the partitioning of a table as part of normalization, what role do the IDs (such as Student ID, Course ID, Faculty ID) typically assume in the new table structure?
Following the partitioning of a table as part of normalization, what role do the IDs (such as Student ID, Course ID, Faculty ID) typically assume in the new table structure?
Flashcards
Normalization in DBMS
Normalization in DBMS
A technique in DBMS to eliminate redundant data, enhancing data integrity and efficiency.
Row Level Duplicacy
Row Level Duplicacy
Occurs when identical rows are present in a table.
Column Level Duplicacy
Column Level Duplicacy
Occurs when the same data is repeated across multiple columns in a table.
Primary Key
Primary Key
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Insertion Anomaly
Insertion Anomaly
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Deletion Anomaly
Deletion Anomaly
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Updation Anomaly
Updation Anomaly
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Study Notes
Normalization Overview
- Normalization is a technique used in DBMS (Database Management Systems) to remove or reduce redundancy in a table
Types of Data Duplicacy
- Row Level Duplicacy: Occurs when identical rows exist in a table
- Column Level Duplicacy Occurs when data is repeated across multiple columns
Row Level Duplicacy Example
- A student table with SID, S.Name, and Age columns can have duplicate rows
- Having two or more rows with the same values for all columns (e.g., SID, S.Name, and Age) constitutes row-level duplicacy.
- Row-level duplicacy should not exist in a table
- Primary keys can solve this issue.
Primary Key Solution
- Primary Key defined as an attribute that is Unique and Not Null
- Setting SID as the primary key prevents duplicate or empty values, resolving the row-level duplicacy
Column Level Duplicacy Example
- A student table with columns such as Student ID, Student Name, Course ID, Course Name, Faculty ID, Faculty Name, and Salary represents column level duplicacy
- Column Level Duplicacy will cause anomalies
- Anomaly is a problem that occurs on a special occasion
Insertion Anomaly
- The inability to insert certain data into the database without inserting other unrelated data
- Example: Cannot enter new course information (Course ID and Course Name) or new faulty information if no students are enrolled in that course
Deletion Anomaly
- The unintentional loss of data due to the deletion of other data
- Deleting a student's record may unintentionally remove information about a course or faculty if that student was the only one associated with them
Updation Anomaly
- Occurs when updating redundant data requires multiple changes in different places, leading to inconsistency if not all updates are successful.
- If Faculty F1's salary needs to be updated from 30,000 to 40,000, the update query will run as many times as F1 appears in the table
Normalization Solution
- Normalization removes redundancy from a table by dividing a table into multiple tables
- Solution to the example above is to separate tables into; SID, S.Name, CID, C.Name, FID, F.name and salary
- After separating, inserting information about a new course, student or Faculty is easy and direct
- Deleting a student won't affect faculty or courses
- Updating salary will only update one table column
- After partitioning each of the IDs becomes a primary key
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