Week 7 Discussion – Denormalization Functionality

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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.

Respond to student below 

Jonathan Sides         

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.

1. "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.