The importance of logical data modeling{1}

by Stefan S
This article it talks about the value of Enterprise Data Warehouse or known as EDW. The benefits implement EDW include cost-effective and powerful platform for everything from predictive analysis to near real-time strategic and tactical decision support throughout the organization. Often time a company struggles with designing and implementing a logical data model or known as LDM. Logical Data Model is vital because enterprise data management rely on it. There are five key challenges to Designing and Implementing a Logical Data Model.

“1. Lack of a common vision for the data warehouse: This has a cascading effect resulting in unclear requirements and a badly designed data warehouse.
2. Organizational muddle: the parent company inheriting a smorgasbord of business and IT resources that may not fit efficiently into the larger organization.
3. Adapting to existing models and migrations: Many Enterprise Data Warehouse implementations include a “forklift” of existing data from the data mart into the Enterprise data Warehouse.
4. Source system-based design: the easiest approach is to look at the existing system for an answer.
5. Trying to create an all-in-one model: For those who don’t understand the value of Logical Data Model, creating hybrid models that combine logical, physical and semantic information in a single model can also be a tempting trap.”
(Logical Data Modeling,2006).

This article can relate to what we learn in class because, creating a Logical Data Modeling for our first project can be very confusing due to the relationship and the normalization that we need to take into consideration. We need to keep in mind that Logical Data Modeling is a key data management discipline, the success of which is critical to ensuring efficient and effective Enterprise Data Warehouse implementation.

Logical data modeling: A key to successful enterprise data warehouse implementations. (2006). Information Management, 16(9), 13-13. Retrieved from