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Database Modeling & Design Fourth Edition- P5

Database Modeling & Design Fourth Edition- P5 | 1.2 The Database Life Cycle 7 Customer cust-no cust-name . Step II c Transformation of the conceptual model to SQL tables create table customer cust_no integer cust_name char 15 cust_addr char 30 sales_name char 15 prod_no integer primary key cust_no foreign key sales_name references salesperson foreign key prod_no references product Product prod-no prod-name qty-in-stock Salesperson sales-name addr dept job-level vacation-days Order order-no sales-name cust-no Step 11 d Normalization of SQL tables Order-product order-no prod-no Decomposition of tables and removal of update anomalies Salesperson sales-name addr dept job-level Sales-vacations job-level vacation-days Step III Physical design Indexing Clustering Partitioning Materialized views Denormalization Figure 1.2 continued number of data dependencies that need to be analyzed. This is accomplished by inserting conceptual data modeling and integration steps steps II a and II b of Figure 1.2 into the tradi 8 CHAPTER 1 Introduction tional relational design approach. The objective of these steps is an accurate representation of reality. Data integrity is preserved through normalization of the candidate tables created when the conceptual data model is transformed into a relational model. The purpose of physical design is to optimize performance as closely as possible. As part of the physical design the global schema can sometimes be refined in limited ways to reflect processing query and transaction requirements if there are obvious large gains to be made in efficiency. This is called denormalization. It consists of selecting dominant processes on the basis of high frequency high volume or explicit priority defining simple extensions to tables that will improve query performance evaluating total cost for query update and storage and considering the side effects such as possible loss of integrity. This is particularly important for Online Analytical Processing OLAP applications. IV. Database implementation monitoring