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Having an adequate data model to serve specific business needs of an organization is important.
Evaluate the need for denormalization within an organization.
Provide at least three examples that prove denormalization is useful to data consumers.
Be sure to respond to at least one of your classmates’ posts.
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Yesterday May 19 at 12:42pm
An adequate data model that serves an organization’s specific business needs is pivotal for various reasons. It allows for streamlined decision-making, enhanced operational efficiency, and improved strategic planning. Yet, it’s equally important to note that not all data models should strictly adhere to normalization rules. Sometimes, denormalization can significantly benefit an organization and its data consumers. Denormalization refers to integrating data from multiple tables into one table, thereby enabling faster retrieval. This may go against the normalization approach of reducing data redundancy, but it can be handy in specific scenarios. Consider the first example of a large-scale e-commerce company. Product searches, page views, and transaction handling require rapid data access in such companies. To provide this, an e-commerce company might denormalize its product data, incorporating product details, reviews, and related product suggestions all within a single table. This could dramatically reduce the time it takes for the server to retrieve and display product data to the end user, enhancing the overall user experience. Consider a scenario involving a large enterprise’s business intelligence unit. Analysts often need to quickly generate comprehensive reports that span multiple aspects of the business. Data stored in a heavily normalized form may require complex, time-consuming queries that combine multiple tables to retrieve the necessary information. Denormalization can simplify this process by consolidating relevant data into fewer tables, making retrieval faster and more efficient. Consider a real-time analytics scenario. Organizations tracking real-time user interactions, such as clicks or page views, must rapidly process high-velocity data. In such situations, denormalization can be advantageous. By reducing the number of necessary databases joins, the organization can process and analyze data faster, providing insights in near real-time.
“Database Systems: The Complete Book” by Hector Garcia-Molina, Jeffrey D. Ullman, and Jennifer Widom. This comprehensive textbook covers a wide range of database topics, including an in-depth discussion on normalization and denormalization.
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