There are various normal forms in DBMS. Each normal form has an importance that helps optimize the database to save storage and reduce redundancies. We explain normalization in DBMS with examples below.
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Data normalization is an essential process for professionals that deal with large amounts of data. For example, crucial business practices such as lead generation, AI and ML automation, and data-driven investing all rely on large sums of data and relational database records. If the database is not organized and normalized, something as small as one deletion in a data cell can set off a sequence of errors for other cells throughout the database. Essentially, in the same way as data quality accounts for the accuracy of the information, data normalization accounts for the organization of said information.
The one-to-many relationship cannot be represented in a single table. For example, in a "class roster" database, we may begin with a table called Teachers, which stores information about teachers (such as name, office, phone, and email). To store the classes taught by each teacher, we could create columns class1, class2, class3, but faces a problem immediately on how many columns to create. On the other hand, if we begin with a table called Classes, which stores information about a class, we could create additional columns to store information about the (one) teacher (such as name, office, phone, and email). However, since a teacher may teach many classes, its data would be duplicated in many rows in table Classes. 2ff7e9595c
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