Task Description
This is a very important step in the data warehousing project. Indeed, it is fair to say that the foundation of the data warehousing system is the data model. A good data model will allow the data warehousing system to grow easily, as well as allowing for good performance.
In data warehousing project, the logical data model is built based on user requirements, and then it is translated into the physical data model. The detailed steps can be found in the Conceptual, Logical, and Physical Data Modeling section.
Part of the data modeling exercise is often the identification of data sources. Sometimes this step is deferred until the ETL step. However, my feeling is that it is better to find out where the data exists, or, better yet, whether they even exist anywhere in the enterprise at all. Should the data not be available, this is a good time to raise the alarm. If this was delayed until the ETL phase, rectifying it will becoming a much tougher and more complex process.
Time Requirement
2 - 6 weeks.
Deliverables
It is essential to have a subject-matter expert as part of the data modeling team. This person can be an outside consultant or can be someone in-house who has extensive experience in the industry. Without this person, it becomes difficult to get a definitive answer on many of the questions, and the entire project gets dragged out.
This is a very important step in the data warehousing project. Indeed, it is fair to say that the foundation of the data warehousing system is the data model. A good data model will allow the data warehousing system to grow easily, as well as allowing for good performance.
In data warehousing project, the logical data model is built based on user requirements, and then it is translated into the physical data model. The detailed steps can be found in the Conceptual, Logical, and Physical Data Modeling section.
Part of the data modeling exercise is often the identification of data sources. Sometimes this step is deferred until the ETL step. However, my feeling is that it is better to find out where the data exists, or, better yet, whether they even exist anywhere in the enterprise at all. Should the data not be available, this is a good time to raise the alarm. If this was delayed until the ETL phase, rectifying it will becoming a much tougher and more complex process.
Time Requirement
2 - 6 weeks.
Deliverables
- Identification of data sources.
- Logical data model.
- Physical data model.
It is essential to have a subject-matter expert as part of the data modeling team. This person can be an outside consultant or can be someone in-house who has extensive experience in the industry. Without this person, it becomes difficult to get a definitive answer on many of the questions, and the entire project gets dragged out.
No comments:
Post a Comment