This Is Attached To A Team Assignment My Portion This Week

This Is Attached To A Team Assignment My Portion This Week Is To Dis

This is attached to a team assignment. My portion this week is to discuss normalization of data. I am looking for someone that is knowledgeable in database and understand what normalization is and what it does. I have attached as much information that I hope you need. If there is more information that is need please ask immediately.

Please review links this provides all information that we have done thus far.... listed below is the assignment and I have underline what I am asking for assist with today. Assignment Your Learning Team has been hired as database consultants for a start-up company that will stream movies over the Internet (similar to Hulu, Netflix, and others). The new organization requires one or more databases for Customer Information, Movie Information, and Supplier Information. At a minimum, the following attributes must be captured: Customer: name, address, customer ID, credit card number and expiration, history of movies rented, "likes" (such as, genres, and movies the customer is interested in) Movie: title, year, supplier ID (owner of movie), description of movie, statistics on movie rental frequency, rental cost Suppler: ID, name, address, bank routing payment information Create the documentation and databases for the following: Conceptual design of the database(s) Data analysis and requirements Entity relationship modeling and normalization Data model verification Database design - justify use or non-use of distributed model Logical design of the database(s) Map the conceptual model to the logical model components. Validate the logical model using normalization. ---------------this is the focus only---------- TUTORS Validate the logical model integrity constraints. Validate the logical model against user requirements. Physical design of the database and description of security, performance, and backup and recovery processes. Include the following processes in your design: Define data storage organization. Define integrity and security measure. Determine performance measures. Define backup and recovery processes. Prototype database(s). Use Microsoft ® SQL Server ® 2012 to create prototypes of the database(s) described in the physical design phase. At minimum, demonstrate use of the following SQL statements: Create database Create index Create table Alter Delete Insert Join Select can upload more details once handshake is complete.

Paper For Above instruction

Database normalization is a fundamental process in designing efficient and reliable databases. It involves organizing data to reduce redundancy, eliminate undesirable characteristics like insertion, update, and deletion anomalies, and ensure data integrity. For a streaming service company, as described in the team assignment, normalization plays a crucial role in structuring the database to support various operations such as customer management, movie cataloging, and supplier details, efficiently and effectively.

Understanding Normalization

Normalization is a systematic approach of decomposing tables to minimize redundancy and dependency by organizing fields and table relationships appropriately. It is achieved through a series of normal forms—First Normal Form (1NF), Second Normal Form (2NF), Third Normal Form (3NF), and higher forms, each defining specific criteria that a table must meet to be considered normalized (Date, 2004). Normalization ensures that each table focuses on a single theme and that data dependencies make sense, which simplifies maintenance and enhances data consistency.

Applying Normalization to the Streaming Service Database

In the context of the movie streaming database, normalization begins with identifying the main entities: Customers, Movies, and Suppliers. Each entity has attributes that must be properly organized into tables. For example, the Customer table initially contains attributes such as name, address, customer ID, credit card number, rental history, and preferences ("likes"). Without normalization, attributes such as "likes" and rental history could result in redundancy and inconsistency.

First Normal Form (1NF)

Achieving 1NF requires that each table has a primary key, and that all columns contain atomic, indivisible values. For instance, preferences like genres or movie interests stored as comma-separated lists violate 1NF since they involve multi-valued attributes. To adhere to 1NF, such data should be stored in separate related tables, such as Customer_Likes or Customer_Preferences. This step ensures the absence of repeating groups and multi-valued attributes.

Second Normal Form (2NF)

2NF builds on 1NF by removing partial dependencies, which occur when non-key attributes depend only on part of a composite primary key. For example, if a table combines customer ID and movie ID as a composite key for rental records, attributes like rental cost or rental date depend solely on the movie or customer, not both. To achieve 2NF, these should be placed in separate tables, preventing redundant data and ensuring that each non-key attribute depends on the entire primary key.

Third Normal Form (3NF)

3NF further eliminates transitive dependencies, where non-key attributes depend on other non-key attributes. For example, if the Customer table has a postal code, and the city and state are stored within it, these are transitively dependent on the postal code. To normalize, such data should be stored in separate lookup tables, ensuring that each piece of information depends solely on primary keys, thus reducing anomalies and simplifying updates.

Normalization Benefits and Challenges in the Context of Streaming Databases

The benefits of normalization in this scenario include efficient storage, elimination of inconsistent data, and simplified maintenance. Since the streaming service will handle numerous transactions daily, normalized structures facilitate quick and reliable data retrievals, essential for real-time recommendations and billing processes.

However, over-normalization can cause performance issues due to excessive joins, especially in read-heavy applications like streaming platforms. To mitigate this, the database design often balances normalization with denormalization, selectively introducing redundancy to optimize performance for specific queries (Batini et al., 2009).

Conclusion

Normalization is a cornerstone of effective database design, particularly relevant for complex applications such as internet streaming services. It ensures data integrity, reduces redundancy, and streamlines maintenance. Proper normalization—progressing through 1NF, 2NF, and 3NF—provides a robust foundation for building scalable, efficient databases that support the operational and analytical needs of a modern streaming platform.

In the context of the team project, applying normalization principles will facilitate the development of a resilient data model that accommodates expanding user bases, diverse content, and evolving business requirements, ultimately contributing to the success of the company's digital streaming goals.

References

• Batini, C., Ceri, S., & Navathe, S. B. (2009). Conceptual Database Design: An Entity-Relationship Approach. ACM Press.
• Date, C. J. (2004). An Introduction to Database Systems (8th ed.). Pearson.
• Elmasri, R., & Navathe, S. B. (2015). Fundamentals of Database Systems (7th ed.). Pearson.
• Relational Database Design and Implementation. Morgan Kaufmann.
• Silberschatz, A., Korth, H. F., & Sudarshan, S. (2010). Database System Concepts (6th ed.). McGraw-Hill Education.
• Connolly, T., & Begg, C. (2014). Database Systems: A Practical Approach to Design, Implementation, and Management (6th ed.). Pearson.
• Fowler, M. (2012). Refactoring: Improving the Design of Existing Code. Addison-Wesley.
• Korth, H. F., & Silberschatz, A. (2010). Database System Concepts. McGraw-Hill.
• Hoffer, J. A., Venkataraman, R., & Topi, H. (2016). Modern Database Management. Pearson.
• Rob, P., & Coronel, C. (2007). Database Systems: Design, Implementation, & Management. Course Technology.