However such data organization in spreadsheet can

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However, such data organization in spreadsheet can lead to various problems which affect the data quality. For example, how would you add information about potential customers who has not ordered yet? It would lead to blank cells for many fields such as book and order information etc. How would you add a book that has been recently received from supplier but has not been ordered by any customer? If you add only book data then a lot of fields would be left blank. Alternatively, if you store the book information in a different spreadsheet then it would lead to duplication of data and related data consistency issues. Think about what would happen if you delete an order such as order # 4 or order # 5. Inadvertently, you will also lose details about some books (such as DBMS Intro book in case of order #4) or some customers (such as john and debbie in case of order #4 and 5). Further, think about modifying an attribute, such as changing price of book named “selfish gene”. You may have to make changes in multiple rows (i.e., row 1 and 5) which increase the update effort. If you forget to change it at even one place, then you will have data inconsistency as same book will have different prices in your spreadsheet and finding the right price at later date may be difficult. 8
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The reason for all these data issues is that data is not structured properly (i.e., un-normalized) when we store such complicated data in a spreadsheet. The problems/anomalies that arise if data is not structured properly (i.e., un-normalized) include: Insertion anomaly: Inability to insert a piece of information about an object that can exist independently of another object without having to artificially insert some information about the other object (Example: Adding a new customer/book before it is ordered) Deletion anomaly: The loss of a piece of information about one object when a piece of information about a different object is deleted (Example: Deleting an order => deleting a customer/book) Update/Modification anomaly: A need to change the same piece of information about an object multiple times (i.e., changing data in a row forces changes to other rows because of duplication) (Example: Changing a book’s price) As mentioned earlier, using a relational database to store such complicated data can avoid such issues. Relational Database Approach is to create a series of logically related two-dimensional tables to store their information. Since this approach can break up the attribute data into various different tables which are connected logically, we can manage database more efficiently without the anomaly that is shown in the method using spreadsheet program. DBMS provides various advantages over spreadsheet. It protects data from misuse, provides simplified access and better interface to data, handles complicated relationship between data, and handles lots of data.
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