Introduction Data Normalization Information Systems and Controls ISC CPA Exam

In this video, we discuss data normalization as it is covered on the information Systems and Controls ISC CPA Exam
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Data normalization is a process used in database design to reduce redundancy and improve data integrity by organizing fields and table relationships. It typically involves applying a series of rules, known as "normal forms." The first three normal forms are especially important for most practical applications.
First Normal Form (1NF) is the first step in the normalization process of database design, which aims to reduce redundancy and improve data integrity. A table is said to be in 1NF if:
Data Atomicity: Each column in the table must hold only atomic (indivisible) values, and each column must contain values of a single type. This means columns should not contain sets of values or lists.
Uniqueness: Each row in the table should be unique. This is often ensured by the use of a primary key.
Importance of 1NF
1NF is foundational for building a robust database structure. Its main benefits and importance include:
Reduction of Redundancy: By ensuring that each column contains only atomic values, 1NF helps in eliminating duplicates within the database. This prevents data inconsistencies that could arise from having multiple instances of the same data element spread across the table.
Simplification of Data Use: When each column holds only one type of information, it simplifies queries and other data manipulation operations. Users and applications can more predictably interact with data because the structure of the database is clearer and more straightforward.
Facilitation of Indexing and Constraints: Databases can more efficiently index tables that adhere to 1NF. This improves performance during query operations. Also, constraints like unique constraints and primary keys are easier to implement when each row is unique and each column holds only atomic values.
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