Transforming Logical Data Models Into Physical Data Models
Transforming Logical Data Models into Physical Data Models
Susan Dash
Ralph Reilly
IT610-1404A-01
According to an article written by Tom Haughey the process for transforming a logical data model into a physical data model is:
The business authorization to proceed is received.
Business requirements are gathered and represented in a logical data model which will completely represent the business data requirements and will be non-redundant.
The logical model is then transformed into a first cut physical model by applying several simple modifications, such as splitting a large table or combining entities in a 1:1 relationship.
The logical model is then transformed into a second cut physical model iteratively applying three levels of optimizations or compromises. The outcome from this is a physical database design:
Apply safe compromises to the model, such as splitting a table or combing two tables.
Apply aggressive compromises to the model such as, adding redundant data.
Apply technical optimizations to the model such as, indices, referential integrity or partitioning.
The physical database design is then converted to a physical structure by generating or writing the DDL and installing the database.
Another website steps had some similarities to the first one I listed. Those steps included:
Assignment of DBMS data types.
Name abbreviation.
Identifying non key indexes.
Assignment of storage (e.g. partitioning and table space assignment).
Generation of the Data Definition Language to create and update the database.
Author Kenneth Kendall describes normalization as a process that eliminates repeating groups found in variable-length records (Kendall 450). Using normalization on your database breaks up your data into several smaller tables, this allows you to avoid redundant data, giving your query less data to scan and allowing you to query only the tables that contain the information you want. This does eliminate the need to scan an entire database each time you run a
Susan Dash
Ralph Reilly
IT610-1404A-01
According to an article written by Tom Haughey the process for transforming a logical data model into a physical data model is:
The business authorization to proceed is received.
Business requirements are gathered and represented in a logical data model which will completely represent the business data requirements and will be non-redundant.
The logical model is then transformed into a first cut physical model by applying several simple modifications, such as splitting a large table or combining entities in a 1:1 relationship.
The logical model is then transformed into a second cut physical model iteratively applying three levels of optimizations or compromises. The outcome from this is a physical database design:
Apply safe compromises to the model, such as splitting a table or combing two tables.
Apply aggressive compromises to the model such as, adding redundant data.
Apply technical optimizations to the model such as, indices, referential integrity or partitioning.
The physical database design is then converted to a physical structure by generating or writing the DDL and installing the database.
Another website steps had some similarities to the first one I listed. Those steps included:
Assignment of DBMS data types.
Name abbreviation.
Identifying non key indexes.
Assignment of storage (e.g. partitioning and table space assignment).
Generation of the Data Definition Language to create and update the database.
Author Kenneth Kendall describes normalization as a process that eliminates repeating groups found in variable-length records (Kendall 450). Using normalization on your database breaks up your data into several smaller tables, this allows you to avoid redundant data, giving your query less data to scan and allowing you to query only the tables that contain the information you want. This does eliminate the need to scan an entire database each time you run a
References: Haughey, T. “Transforming a Logical Data Model to a Physical Database Design - an Overview”. www.tdan.com/view-featured-columns/5389 Kendall, K., & Kendall, J. (2005). Systems Analysis and Design (Sixth ed., p. 450, 474). Upper Saddle River: Prentice Hall.