This Is The Grading Requirements And Attached Below Is the Hw1fragmen This is the grading requirements and attached below is the hw 1. Fragmentation strategy- Rationale for fragmentation choices is clearly tied to the facts in the business case. considerations for horizontal, vertical and mixed approaches were explored. 2. Replication strategy- Replication choices are clearly linked to business needs. If no replication is recommended, the reasons why are discussed 3. Schema- The schema is complete, well organized and consistent with all aspects of the fragmentation/replication strategy 4. Distributed transaction- Example transaction is complete and shows an understanding of a 2-phase commit protocol. The approach would keep distributed/replicated data consistent
Paper For Above instruction Introduction Effective database design in distributed systems demands strategic fragmentation and replication to optimize performance, ensure data integrity, and meet business requirements. This paper evaluates various fragmentation strategies—horizontal, vertical, and mixed—and their alignment with specific business cases. It also explores how replication choices, or the decision not to replicate, address business needs. Furthermore, the design includes a comprehensive schema reflecting the chosen strategies and exemplifies a distributed transaction using a two-phase commit protocol to demonstrate data consistency across distributed environments. Fragmentation Strategy Fragmentation involves partitioning a database into smaller, manageable pieces to improve manageability, performance, and security. The choice of fragmentation strategy hinges on the underlying business case's facts, such as query patterns, data distribution, access frequency, and security requirements. For example, horizontal fragmentation divides a table into subsets of rows, which is beneficial when different data segments are accessed by different geographic locations or units within an organization. In a retail business with multiple stores, customer data could be horizontally fragmented by store location—each store manages its own customer records, reducing data access latency and enhancing local data management. Conversely, vertical fragmentation partitions the table by columns, ideal when certain attributes are frequently accessed independently or by different user groups. For instance, sensitive customer payment information might be stored separately from non-sensitive demographic data for