The Data Modeling Addict – April 2012

Excerpt from Data Modeling for the Business: A Handbook for Aligning the Business with IT using High-Level Data Models

This is the sixth in a series of articles covering the ten steps for completing the High-Level Data Model (HDM), which is also known as a subject area model or conceptual data model. In our article series so far, we covered an overview of the HDM and four of the ten steps to building one: Identify Model Purpose, Identify Model Stakeholders, Inventory Available Resources, and Determine Type of Model. In this article we will discuss the fifth step, Select Approach. Here are all ten steps as a reference (the step in bold is the focus on this article):
  1. Identify model purpose
  2. Identify model stakeholders 
  3. Inventory available resources 
  4. Determine type of model
  5. Select approach
  6. Complete an audience-view HDM 
  7. Incorporate enterprise terminology 
  8. Signoff
  9. Market 
  10. Maintain
There are three approaches for building a high-level data model: top-down, bottom-up and hybrid. Even though these approaches sound completely different from each other, there is really quite a lot in common across them. In fact, the major difference between the approaches lies in the initial information gathering step.

The top-down approach starts with a purely business need perspective. We learn how the business works and what the business needs from business people, either through direct meetings with the business, or indirectly through requirements documents and reports. The business is allowed to dream and all requirements are considered possible and doable. If a business user discovered an old lamp while looking for shells on the beach, and upon rubbing the lamp a genie appeared and granted the user three wishes, at least one of these wishes should match their ideal set of requirements for an application. This is what we want to capture. The business should aim for the sky.

Ideas are accepted even if we know there is no way to deliver the requirement in today’s application environment. For example, imagine if a business user describes their business with the concept of ‘Consumer’ as the focal point. Although you know today there is very little information being captured on Consumer, it is still important to capture the concept on the HDM because it could be how the business should work as opposed to currently works today.

The bottom-up approach, on the other hand, temporarily ignores what the business needs and instead focuses on the existing systems environment. We build an initial high-level data model by studying the systems that the business is using today. It can include operational systems that run the day-to-day business or it can include reporting systems that allow the business to view how well the organization is doing. Once the existing systems are understood at a high level, new concepts can be introduced or existing concepts modified to meet the business needs. For example, ‘Consumer’ may not appear on the initial bottom-up model. After reviewing this model with the business, they might then identify that Consumer is indeed something that should be included.

The hybrid approach is iterative and usually completes the initial information gathering step by starting with some top-down analysis and then some bottom-up analysis, and then some top-down analysis, etc., until the information gathering is complete. First, there is some top-down work to understand project scope and high-level business needs. Then, there is a need to work bottom-up to understand the existing systems. The whole process is a constant loop of reconciling what the business needs with what information is available.

The figure below summarizes these three information-gathering approaches.

Figure 1: Information-Gathering Approaches

When to Choose Which Approach

If there are minimal business resources available and ample systems documentation, and the purpose of the model is to understand an existing application, a bottom-up approach is ideal. If a new system is being built from scratch and there are business experts eager to participate in the project, a top-down approach would be more appropriate. If a new system is being planned, or an upgrade to an existing system, and business expertise is available and required, a hybrid approach is best. Most high-level models tend to be built using the hybrid approach because there is a need to understand the existing application environment before building something new.

When you have both ample business and IT resources available, we would recommend you choose the hybrid approach. It has a nice balance of top-down and bottom-up and therefore chances increase that you’ll build the right model.


Order processing is currently performed with many manual activities. Although eventually there will be an application to automate these activities, your first step is to understand the existing business process. Business resources are anxious to participate.

Because our goal is to capture an existing business process and there are ample business resources available, it makes sense to use the top-down approach. Through meetings with business resources and by extracting concepts out of business and functional requirements documents, one can complete this order processing HDM.

In the next column I will go into detail on Step 6, Complete an audience-view HDM.

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Steve Hoberman

Steve Hoberman

Steve Hoberman has trained more than 10,000 people in data modeling since 1992. Steve is known for his entertaining and interactive teaching style (watch out for flying candy!), and organizations around the globe have brought Steve in to teach his Data Modeling Master Class, which is recognized as the most comprehensive data modeling course in the industry. Steve is the author of nine books on data modeling, including the bestseller Data Modeling Made Simple. Steve is also the author of the bestseller, Blockchainopoly. One of Steve’s frequent data modeling consulting assignments is to review data models using his Data Model Scorecard® technique. He is the founder of the Design Challenges group, Conference Chair of the Data Modeling Zone conferences, director of Technics Publications, and recipient of the Data Administration Management Association (DAMA) International Professional Achievement Award. He can be reached at

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