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Low Code Isn’t Dead Yet: Or Is It?

Throughout the years, there have been various attempts to make programming streamlined and digestible for everyone. Few people have the time and patience to hunch over the laptop for months, years, and zillion hours to acquire coding skills and know-how. This ushered in the budding trend of low-code platforms. The trend has quickly evolved towards data sciences and analytics, reducing the pressure, time, and cost.

How do we use low coding in data analytics?

Low-code is an approach to creating, configuring, and modifying systems and applications that require little or no programming code. Low-code platforms use visual interfaces with simple logic and drag-and-drop features instead of various programming languages. These intuitive tools allow non-tech-savvy users to create their own applications for a variety of purposes. No wonder, this one has quickly become the disruptive technology for businesses to digitize the way they do business.

This philosophy has been applicable to lots of bottlenecks, including data. Since every application leans heavily on data, a powerful integration sets the project for success or failure. Due to huge scaling requirements, a broad spectrum of data formats, and various kinds of endpoints data integration has become increasingly complex.

Low-code techniques allow us to keep the tech architecture clean and transparent, reduce maintenance efforts and make data integration tangible for business users.

No-code Eats Low-Code For Breakfast?

At first glance, it’s easy to confuse low-code and no-code. Even the big analyst firms like Gartner seem to have a hard time telling them apart. That is why we’ve gone an extra mile to compile the major differences of low-code vs no-code and dumped them in a succinct list of differences below.

Low-code vs. No-code

Target audience: Developers vs Non-technical employees
Main aim: Speed of development vs Ease of use
Customization: Total customization available vs Pre-built templates can be customised
Programming skills: Required vs No skills
Platform lock-in: Flexibility vs Limited to one platform
End-to-end development: Present vs Limited capabilities
App complexity: Simple to complex vs Simple
Cost-effectiveness: A safe bet for an operating dev team vs Ideal for backlogged dev team

Although both technologies are created with the same thing in mind, which is speed, they are geared towards different segments. As you can see from the table, no-code platforms cater to citizen developers, thus being usable by anyone with no technical knowledge required. Low-code platforms, on the other hand, allow for more complex applications and customization. Therefore, only tech-savvy users can benefit from them.

As for the real use cases, both technologies have found favor with organizations. Thus, low-code is typically used for apps that are foundational or run important processes for a business and are mission-critical, whereas no-code has been used for applications that evolve with frequent updates and changes in use-case.

Along the same lines, we'd like to express our thanks to Flatfile for sponsoring this newsletter. Flatfile Concierge seamlessly migrates customer data using a secure, collaborative, no-code environment. Ready to solve data chaos in minutes?

So, Which One Should I Choose?

In practice, that is not a question with a clear-cut answer. After all, no-code platforms have been inspired by low-code ones in which pre-building has taken the place of the customization through coding. Therefore, when making the right call, be sure to know exactly who’s going to use it and what it will be used for.

But there’s one thing we know for sure. We’ve stepped into the new era where hand-coding will eventually go MIA. Almost. But that’s a whole different story.

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