Data Modeling

 

Data Modeling

  

So, what exactly is data modeling?

 

Well, it's simply a way to structure and organize your data. It provides you with a structural foundation in graphical form that you can use as you build out your application correctly - the first time.

Data modeling provides the structural foundation - in graphical form - of what you're going to build in QuickBase.

There are three (3) types of data models:

• Conceptual
• Logical
• Physical

 

Conceptual models aim to provide context as to the business understanding of data, not a technical one.  These are used to facilitate a discussion among businesspeople about their systems, processes, and organizations.

Logical data models describe entities and attributes and the relationships that bind them.

While the physical models then implement the logical model as tables, fields, field types and relationships.  We are going to focus on the physical model, as it relates to QuickBase, implementing the logical model as tables, fields, field types and relationships in a QuickBase application.

 

The #1 value is identifying which entities are your tables, and how are they related. This tremendously helps builders who are new to our platform, when building their first apps.

 

Let's get started…

 

So, where do we start? How do we make sense of our data?

 

The first step is to write down, to articulate, what it is that you are attempting to do.  Using plain language, simply state what the business problem is that you are trying to solve, and what a desired solution may involve.  There is no need to get overly detailed at this point in the process, but you will want to make sure that you clearly state what it is that you are setting out to do.

 

Then, begin by simply observing the language that was used to describe the business problem we are attempting to solve. By looking for the nouns – the people, places or things – that used.

 

By observing the words used in your description, you will begin to see patterns or trends in the language, and these terms will serve as common denominators, as categories or buckets and they may become your tables in QuickBase.

 

All of this do this already every day – on our computers we all have created file folders to structure and organize our data so that we may search and retrieve what we're looking for quickly, and efficiently.  This exercise is going to help us identify the tables we will use in QuickBase.

 

After categorizing all of your data into their appropriate groups, let's now turn our attention to relating these groups to one another.  This is sometimes referred to as determining the cardinality in your data model.

 

This is a practice in identifying the table-to-table relationships that help structure your data, commonly the "1-to-Many" we articulate when building a new relationship in QuickBase.  You will want to simply say out loud what the possible relationships are, because as you listen to yourself state these out loud, it will be clear to you which 'direction' each relationship should be.

 

Many folks are eager to get started and jump right into QuickBase and begin building, without taking the time to plan their application.  This will inevitably lead to some mistakes, and the applications can quickly grow out of control as more functionality is added and the app evolves over time.   This can make applications difficult to manage as they become more complex.

 

Taking the time to plan out your application will help guide you as the needs of the system grow and more tables are included in the solution.  Creating an effective data model not only benefits you in building new apps from scratch, but also is invaluable in reverse engineering an application you've inherited. Take the time to create an effective data model, it will pay dividends in the future!

 

 

------------------------------
Sean Padian
------------------------------