There are ten steps that are required to successfully develop a high-level data model. Although you can start some of the steps out of sequence, they need to be completed in the order they appear. For example, you might find yourself jotting down stakeholders (Step 2) before identifying the purpose of the model (Step 1). However, you will need to revisit your model stakeholder list after finalizing the purpose of the model.
The ten steps for completing the high-level data model are as follows:
Step 1: Identify Model Purpose
Determine and agree on the primary reason for having a high-level data model. Always begin with the end in mind.
It is important to remember to focus the purpose of the high-level data model around a business need or process improvement. Data models are built to ensure that everyone has a precise understanding of terminology and business rules.
One of the fascinating outcomes of this first step is realizing that the model’s stakeholders see the world very differently from each other. It is not worth investing time and money in the other nine steps without a clear, agreed-upon reason for the model. That doesn’t mean the high-level data model cannot have more than one purpose, but there should be one primary purpose for building it.
Once there’s consensus on the purpose of the data model and it is documented, you need to determine whether a top-down, bottom-up or hybrid approach is ideal. Matching the right factors with the right modeling approach will dramatically increase the probability of having a successful model.
Here are the most common reasons for building a high-level data model (remember, communication is the main reason behind each of these):
- Capture existing business terminology and rules.
- Capture proposed business terminology and rules.
- Capture existing application terminology and rules.
- Capture proposed application terminology and rules.
Step 2: Identify Model Stakeholders
Document the names and departments of those who will be involved in building the high-level data model, as well as those who will use it after its completion.
A high-level data model stakeholder is someone who will be affected directly or indirectly by the model that is produced during the modeling sessions.
As you might expect, when the purpose of the high-level data model is to capture an existing or proposed section of the business, the builders tend to be people who know the business, such as business analysts and business users. Similarly, when the purpose of the high-level data model is to capture an existing or proposed application, the builders tend to be more technical, such as developers and database administrators. The users of the model though, could be anyone from business or IT.
Those with more of a business-oriented background can help build the business-focused view and those with more of a technical background can help build the application-focused view.
All or some of those users should also be your stakeholders and are required to sign off on the model.
Step 3: Inventory Available Resources
Leverage the results of step 2 to determine what people will be involved in building the high-level data model and also identify any documentation that could provide useful content to the model.
Now that you have identified why you are building the model and who will be involved in building and using it, you need to identify the resources you will be using. The two types of resources are: people and documentation.
People include representatives from both business and IT. Businesspeople may be management and/or knowledge users. IT resources can span the entire IT spectrum, from analysts through developers, from program sponsors to team leads.
Documentation includes systems documentation or requirements documents. Systems documentation can take the form of standard vendor documentation for a packaged piece of software, or documentation written to support a legacy application. Requirements documents span business, functional and technical requirements and can be an essential input to building the high-level data model.
Step 4: Determine Type of Model
Determine which of the four types of high-level data models will work best based on the purpose of the model and the available resources.
The purpose of the model identified in step 1 aids in determining the type of model to build in step 4. The four different variations include:
Relational data model. A relational data model describes the operational databases that support business processes.
Dimensional data model. A dimensional model is used exclusively for reporting.
Business perspective. A business perspective is a high-level data model of a defined portion of the business. Choose the business perspective for any of the following situations:
- Understanding a business area.
- Designing an enterprise model.
- Starting a new development effort.
Application perspective. An application perspective is a high-level data model of a defined portion of a particular application. Choose the application perspective for any of the following situations:
- Understanding an application.
- Starting a new development effort.
Step 5: Select Approach
Chose either a top-down, bottom-up or hybrid approach based on the purpose of the model and the available resources.
Even though the three approaches for building a high-level data model sound completely different from each other, they have a lot in common. In fact, the major difference between the approaches lies in the initial information-gathering step.
