Why Data Modeling Fall Sideways?

One of the most surprising aspects I have come to expect during the years of data integration and warehousing consulting is how little data modeling is actually being practiced in this field. While it is hard to find a database technologist who would argue that data modeling is “bad” or “wrong”, it is simply not practiced. When I ask for the model of the existing database, the usual response is in the form of a 4-5 years old ER diagram that is completely outdated (at best) accompanied by an embarrassed shrug. It is one of the most basic and fundamental things to do when approaching any data problem, and yet companies are always impressed by this and are surprised by the huge benefit and value the model brings to the development process. Don’t they know how important data modeling is? Of course they do. So why don’t they practice it?

I think there are many explanations to this puzzling question, and I would like to offer a few. As you would expect the answers are not related to technical competence, or lack of appreciation for the fundamentals of good development practice. It has more to do with the reality of corporations, and the pressures of IT operations.

Lack of time to model

The fact of the matter is that you do not have time NOT to model.

The fire alarm doesn’t stop ringing. The users are constantly demanding increased functionality and services, “threatening” to replace internal IT services with external “Cloud” services or outsourced solutions. You need to deliver results every two weeks. In that kind of an environment, where you can barely plan how your day will end, you don’t have time to model. Or so goes the argument. It is not always spelled out and conscious, but it is a big reason why modeling falls sideways. The “lack of time argument”. You understand how good modeling practices can save you time in the long run, and keep your development streamlined and your environment maintainable, but you simply don’t have the luxury of long time planning right now.

While it’s absolutely clear why modeling saves you time in the long term, it will also save you LOTS of time in the short term. Databases are not built in vacuum. They are used to house information and data that will need to be consumed by users through applications. And unless you have only one person who does all the work, a data model is the ONLY way your various team members and participants in your data driven application will be able to make progress together and IN PARALLEL.

The data model becomes the contract between the application and the data it represents. It shields and separates the various parties that are collaborating to realize the latest initiative, and allows them to make progress in parallel, without needing to wait for each portion of the work to be completed before they can proceed.

Lack of tools

This does not come up often, but I still run into this sometimes. Enterprise modeling tools are typically expensive and are complex to learn and use. Licensing restrictions prevent many people in the organization from using them and lack of functionality, or training, causes database administrators and developers to eventually stop using them.

Keeping up the model can be a lot of work, but it is the only way to keep everyone informed about what is going on in the database, and how it evolves and changes over time. When it’s time to work on a new initiative, everyone can go to one place and understand the state of the information.

And while you will need a tool to store and maintain your model, especially the physical one, the most important modeling tool you can ever have is your whiteboard.

Modeling ALWAYS starts on the whiteboard. There is simply no better tool for collaborative data modeling then standing in front of a whiteboard with a dry erase marker, and a group of other talented database developers all standing or sitting around, shooting down approaches or embracing new ideas, erasing, tweaking and refining until they crystalize to a reality everyone can understand.

Lack of discipline

Modeling takes a lot of practice, and a lot of discipline. It is a bit counter instinctive for a super star developer. Their instinct, when presented with a technical challenge, is to “jump right in” and solve it in a blazing flash of genius. So the discipline to take time to see how this “fits the model” takes an extra effort upfront, which is very easily dismissed.

If you can embrace the ideas that modeling can help speed up your development cycles and can be done using simple tools like a whiteboard, you will be that much closer also accepting the fact you will need to nurture a culture that encourages discipline around modeling. Before you know it you will be moving out of a reactionary fire drill mode, and into a proactive and thoughtful mode, where you can help deliver information that matters to your organization most strategic needs.

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