What’s Better: Low-Code or No-Code Data App Development?

The world of data app development is ever-evolving and as such, it is becoming more democratized. And within businesses, this can often lead to the question whether to go low-code or no-code? This prevalent debate is central to the broader field of software, but it has a particular impact on data science, and teams developing data apps.

For data scientists who use Python for their data exploration and analysis but are less familiar with front-end coding, the choice between low-code and no-code solutions can help teams quickly and easily build custom data applications without being limited by the coding knowledge required for the front-end interface.

In this article, we’ll explore the debate around low-code versus no-code data app development, and offer insights and solutions to help teams develop a streamlined path that turns their analytics into functional, production-ready data apps.

What is low-code data app development?

Low-code development allows users to create data applications with minimal manual coding and development work to deploy such apps.

In the context of data science, the main concept behind low-code data app development is to simplify and accelerate the development cycle. Usually, this will involve visual, drag-and-drop interfaces and other pre-built components that remove the need for IT involvement in deploying data science apps to production.

Low-code data app development allows data scientists to focus on their core competencies by writing machine learning models or other data science models with Python or other data science languages. 

By allowing data scientists and analysts to focus on their analyses, low-code development empowers data scientists and analysts to easily share their findings by building data apps with intuitive and responsive UI, rather than merely sharing screenshots or depending on IT teams to deploy their models.

Low-code ultimately gives data science and analytics teams the freedom to communicate their recommendations without having to worry about building full-stack applications or depending on developers.

What is a low-code development platform?

A low-code development platform is a software solution that means users can create, design, and deploy data apps with minimal coding and programming effort. A low-code development environment tends to provide a visual, user-friendly Graphical User Interface (GUI) where developers of varying expertise can build apps through a combination of pre-built components. 

Low-code platforms often include code autogeneration capabilities for database integration, user interface design, and backend services. They also cater to a wide range of data science applications, from simple reports to interactive interfaces for complex models running in real time, which makes them accessible to a more diverse audience. 

What is no-code development?

No-code development empowers people with little to no coding experience to build data apps by removing traditional programming languages from the app development process.

No-code platforms let their users, often referred to as "citizen developers," design and deploy a wide range of apps. The key principle of no-code development is that it is accessible and democratized. It enables almost anyone to develop an app, and reduce their reliance on IT departments and coders. Like low-code solutions, the main benefit of this is that it accelerates the development cycle of apps.

What is a no-code development platform?

A no-code development platform allows people to build apps without the need for traditional coding or programming skills. No-code platforms tend to use visual interfaces, drag-and-drop functionality, and pre-built components to help inexperienced users develop apps easily.

No-code platforms are renowned for being accessible, and emphasizing a more user-centric approach to software development. As such, the no-code approach is often used by businesses who might not have access to an expensive team of codes, but that need to streamline their process or quickly adapt to changing market demands.

What are the benefits and challenges of low-code vs no-code data app development?

Benefits of low-code

1. Customization: With low-code, you can make your data app fit your exact needs. It's great for apps that require more flexibility and some bespoke elements.
2. Coding support:  Developers can still add in some custom code when they need to on low-code platforms. This gives them more control over how their app works.
3. Faster development: Speed is a key advantage, as low-code makes it faster to develop your app so you can get it to market quicker.
4. Integration: Low-code platforms make it easier to link up your app with different data sources, APIs, and other systems so they all work together.
5. Scalability: Whether you're a big business or you're planning to grow, low-code can handle it. 
6. Advanced features: If you need your app to handle a lot of data and be production-ready with ironclad security features, low-code is a better choice.
7. Comprehensive solutions: Low-code is better if you need your app to do a bit of everything, whether that’s managing databases to handling workflows.

Benefits of no-code

1. Accessibility: Non-technical team members can still build simple data apps using a no-code platform.
2. Simplicity: Because they are designed for almost anyone to use, it’s faster and easier to develop apps using no-code systems.
3. Reduced costs: Though you might need to pay a fee to use some no-code platforms, they remove the need for more expensive coding and development teams.
4. Empowerment: With a no-code platform, almost anyone in your business will be able to have a go at app development.
5. Standardized components: Pre-built elements and templates in no-code platforms act like building blocks that help keep everything consistent (and easy to use).
6. Agility: The market changes quickly, and with a no-code platform you can tweak and adapt your app in no time.

Challenges of low-code

• Although it's more accessible than traditional coding, low-code platforms still need their users to be able to run a base level of commands.
• Low-code data apps might be less accessible to business users, as they are ideal for data science teams with the ability to build the underlying scripts needed to execute the model behind teh app interface.
• Some low-code platforms are not able to scale as seamlessly as your app might need, without IT help. This is especially common for low-code apps that are asked to deal with large user bases or more advanced systems.

Challenges of no-code

• The amount of customization offered by no-code platforms is usually limited. This means it’s not a great choice for data apps that need bespoke features or functions.
• It can be hard to integrate no-code apps with legacy systems or external APIs because they tend to be less flexible.
• No-code platforms are more at risk of low security. This is a drawback if your app is sensitive, or your industry requires tight security measures.
• No-code platforms aren’t always capable of handling complex or production-grade apps. This will make it harder to scale when the time comes.

Types of users

Whether you choose to develop your app using low-code or no-code comes down to how proficient you and your team are with traditional code. If your team has some coding ability, or if you’re working on a slightly more complicated project then low-code will be best. If your app is simple and doesn’t require much technical skill then no-code should work just fine. Both approaches are valuable for businesses without a software development team, but they appeal to different types of app developers. 

Users of low-code:

• Large enterprises
• Data scientists and analysts
• Business analysts
• Custom data app developers

Users of no-code:

• Business professionals
• Subject-matter experts (e.g. in specific areas like finance, healthcare, or education)
• Entrepreneurs and small business owners
• Data analysts
• Startup founders and early-stage teams
• Teachers and educational institutions

Limitations of low-code vs no-code app development

Drawbacks of low-code vs. no-code

There are drawbacks to both low-code and no-code development, which vary depending on your business and the kind of app you’re trying to create. Low-code is versatile, and can be pretty easy to use for simpler use cases, but it can still require custom coding for highly complicated projects. Users of low-code platforms will need to learn how to use the tools, which can be harder than those in no-code systems. 

On the other hand, no-code platforms put a limit on how much you can customize your app, which makes them less suitable for projects that have specific or bespoke needs. It can also be harder to integrate a no-code app with your existing systems, and there might be security issues and limitations on how much your app can scale.

Which should you choose, low-code or no-code data app development?

The choice between these two coding platforms should come down to which fits best with the requirements of your project. Especially consider whether it needs to be customized, whether you plan to scale the data app, and the technical expertise of your team.

What is a data app? 

Data apps are a cross-over between web apps and traditional dashboards. They make it easier for decision makers and business operators to see and understand their company’s data. These apps have an accessible user interface that makes it easier for non-technical team members to use. This means that more people within a business can make data-driven decisions, without being experts in data science.

Pros and cons of low-code vs no-code for data app development

If you’re dealing with voluminous, multi-dimensional data from different departments or need custom elements, low-code development platforms are the way to go. They're a great go-to for creating customized visuals and interactive features, with good levels of security. Plus, they give data scientists the power to build apps that match their business's needs.

But if you're just getting started with data analysis, are doing some basic metric reporting, or you've got a smaller team, then no-code platforms are your best bet. They're perfect for people who are new to the analytics game, as they make it super easy to learn and experiment quickly. No-code is a natural fit for teams working with small amounts of data and specific tasks, when simplicity, accessibility, and speedy development are essential.

Stay tuned — we’ll go into more detail on best practices to develop a low-code app in part two: The Key to Rapidly Build Low-Code Data Science Apps.