How to build a perfect data model easily in a few steps

What’s a Data model?

A data model is an abstract description of how your program stores, connect to, organizes, and manages data. This includes your values, where they came from, and how they are put together.

The schema of a database is different:

The schema is only about one source, but the data model is about all of them.

The data model is based on the structure of the data, not the details of the source.

Set up a base for your project’s data processing. Use this to build the automated parts of your app and the user interfaces.

Why use data models?

Why design a data model? All apps have data models. You just have to think about how to make the best one for your needs.

This affects how secure, functional, fast, scalable, and easy to use an app is.

So, it pays off to start with a good data model.

Especially when getting information from sources inside an app. Some of the information you need might be in external sources or an internal database.

In data modeling, it’s important to know what data you need and where it will come from.

A good data model makes sure that the system is compatible, works well, can grow, and is safe.

Here are the steps you can take and important things to think about when making the right data model for your next app project.

  1. Collect Business requirements

First, make a list of the business requirements for how your application will process data. Since we don’t need specific variables yet, requirements can be general.

Finding out what your app will do and what data it will need is part of gathering requirements.

Business stakeholders like end-users, decision-makers, clients, and technical colleagues must be consulted to figure out how the app will work.

  1. Set up processes

Then, we might start figuring out how things work. Creating a plan for how the application will respond to events and triggers. This includes both system responses and user responses.

Again, in a general way, without any specifics.

This step is data modeling that makes sense.

We’ll use this information to make a more concrete data structure.

For now, we can describe how we want things to work without using business jargon.

Our example timesheet could be used for several business tasks:

Labor costs should be added up on every timesheet.

Project management should be notified by a useful timesheet.

Costs and time should be easy for project managers to keep track of.

Changes to submissions should only be made by employees. Project managers should change submissions that are important.

Based on the timesheets for each project, the system should send invoices through other platforms.

These are just some examples of business rules. Logical modeling shows how our program will react to user actions and any operations that happen in the background.

  1. Make a conceptual data model.

Create a conceptual data model next. This is a more organized plan for getting the processes we figured out in the last step to work. For now, we’ll use simple business terms. The next part is about the details.

A conceptual model is about putting together facts in a way that helps us reach our goals.

First, choose the broad entities in our data. Then we could write down what we need to know about each and start making simple connections.

So, our timesheets app must have the following:

Projects, Owners, Employees, and Timesheets.

Your business may require more entities. Tasks for the project and other tools.

Then, we’ll draw a sketch of the data for each entity. For example, the personal information of your employees, their hourly rates, the needs of a project, its budget, and its goals.

Lastly, your conceptual model should show how entities are connected to each other. There is an owner for each project, and employees can turn in more than one timesheet.

  1. Explain what entities and attributes are.

Once we know what our entities are, we can define them. Most of the time, each entity is put into a database table. A row will be used to show each employee or project.

Each column will hold a different attribute of the entity. We must decide:

We need to know how they are set up, what their names are, and how they work.

If you build a new application database, it will be part of your schema. Think about this when deciding where to get the data you already have.

  1. Find data sources.

For your app to work, you need to know where values come from and how to store them. Locating your app’s data sources.


Flat files, APIs, web services, internal and external databases, and other company assets.

These are our main sources of data. When we’re done, our app can ask them questions to add or change values.


Here, it’s important to choose between new and old data sources. Both can be a part of our data model.

There are many ways to get the same results.

Let’s brainstorm employee timesheet data source structures.

The easiest way to handle the things we found is to make an internal database for them. We’d have the most control over how our attributes and entities are stored because we’d have to build our own database schema.

This would also make it hard to connect platforms.

We could connect to an outside database directly or through an API.

If a relevant database exists. We don’t have to make our own. It works well with other programs that ask for the same information.

Existing database schemas may not meet our demands. We would have to change the way query outputs are set up to meet our needs.

Most often, we need both. Our timesheet app may get information about people and projects from outside sources, but it will save information from users in an internal database.

We also have a guide for putting databases together.

  1. Link entities

We talked briefly about how data model entities relate to each other. We can build more detailed relationships between our entities if we have a more technical view of them.

Here are some things to keep in mind.

First, each set of entities needs the right relationship between them. A few options:

1:1. \sMany-to-one.


We also have to decide which columns in each table will be used to build the links. Specifics to DBMS apply.

A SQL database must have a primary key for each row. The rows in other tables are linked to by these unique values. Foreign keys are the main keys in tables that are linked together.

For multi-database data models, relationships must be set up. Putting together an internal database so that entities from different sources can be queried and stored.

An entity-relationship model can be used to describe the entities and the relationships between them in a certain field of study. The ER diagram online can be used to show how different things or people in a system are linked to each other.

Entity types and the relationships between them are the building blocks of any entity-relationship model.

  1. Create a physical data model.

This gives details about the internal database structure and how to connect to external data sources.

To make a physical model, you have to use the steps above.

When you design the database for your app, this means giving all attribute names, types, formats, integrity constraints, and other limits.

In our guide, we talk about database schemas.

We also need to think about how to connect our app to outside data sources. The code for our app can be changed to point to the source’s name, location, authentication information, and other details.

With low-code tools and other new app-building platforms, we can use dedicated data interfaces.

These customized interfaces connect to external data that is unique to each user. You can enter information on a GUI instead of writing code.

Then, depending on the tool and data source, you can make queries by hand or import all queries from the source.

  1. Data normalization and integrity

Set up a data model to make sure that your app will be valid, reliable, and honest for a long time. Avoid things like duplication, conflicts, bad formatting, etc.

Data normalization can help.

Normalization is worth talking about. This is a list of ways to keep data from being duplicated or odd.

Here are some ways to do it.

A data structure is the one that is used most often. The goal is to make things that have a single idea or theme. If you’ve done what we told you to do, this is already in your data model.

When a group of values applies to more than one row in a table, make a separate entity and use relationships to link it to the original table.

This makes things run faster and takes up less space.

In a personnel directory, each row may have the name of a department, the phone number for that department, and the properties of the department head.

We would have to put the same information in the employee details table twice.

There’s no need to list or change the company’s departments.

So, it’s better to make a table for each department and link each employee’s record to it. This simplifies queries, maintenance, and server burden.

  1. Data model upkeep

Your data model is still hard to keep up with. This makes it hard to scale up an application. For example, you could add more data and features to your app.

You must adapt without damaging your data model.

It is possible to add, edit, or change objects, relationships, or properties.

Make sure your data model is flexible. Adding more features, entities, attributes, processes, or connections.

You must be able to change what needs to be changed without changing other data. With transitive dependence, changing one thing can change something else.

For a third-party tool to work, you may need to change the format of an attribute. If you do this, other data model elements that use this attribute might stop working.

Preventive steps are very important.

After this, you must make sure that the server has enough space for more users and storage. Preventing data migrations requires adequate modeling.

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