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Low-code: Panacea or Revisited Hype? Low-code: Panacea or Revisited Hype?
I’m hearing a lot of rumblings in the industry lately about so-called “low-code/no-code” application development platforms. These solutions are purported to enable software creation... Low-code: Panacea or Revisited Hype?

I’m hearing a lot of rumblings in the industry lately about so-called “low-code/no-code” application development platforms. These solutions are purported to enable software creation through point-and-click user interfaces instead of traditional programming, thus reducing the amount of hand-coding required to develop a new piece of software. Enterprises are always in search of new ways to innovate, and we’re being told that leading companies are putting low-code development at the core of their digital strategy. Some of the alleged attractions for low-code platforms are:

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  • Visually oriented drag-and-drop development tools rather than traditional hand coding.
  • Versatility with the combined power of data integration platforms, ETL tools, and BPM applications.
  • Speed to deployment, allowing for enterprise-level application development delivered in days or weeks, instead of months or years. 

While this remains an emerging market space that is continuing to evolve, many analysts see it crossing into the mainstream as more enterprises become comfortable with the low-code mantra and are beginning to adopt low-code approaches in various forms. As a result, we’re hearing there is an acceleration to embed low-code solutions into a broad spectrum of applications, e.g. sales, marketing, and business process management platforms, as well as solutions for data integration, data science, content management, analytics, robotic process automation, and cognitive platforms, along with many others.

All of this sounds great, but we should think hard before deciding whether low-code solutions are a great panacea, or just revisited hype. In this article, I’ll take a closer look at this technology with an important historical caveat.

A Quick Drill Down on the Promise of Low-code

I keep hearing about how low-code helps application development proceed at a faster pace. Enterprises want to be in complete control, while software engineers want to have the ability to automate many of the traditional business needs. This can come with a cost to agility and scalability depending on the approaches used. Implementing automation across software applications can be difficult, even if you have a dedicated team of developers on staff to implement. To this end, engineers need to find a way to achieve greater automation to transform complex processes and services into simple, self-serviceable, automated workflows. Believers say low-code automation will be a key driver for many strategies looking to ensure streamlined application development.

Bridging the gap between no-code, low-code and professional coders, this class of tool brings together a variety of resources to enable business analysts and developers alike to equally collaborate in the application creation process.

Integration is becoming a pervasive problem across businesses, and that means integration tools will need to accommodate multiple user types along with traditional developers. Therefore, integration vendors will need to provide tooling for ad hoc and non-technical developers as well as specialists, including graphical, low code solutions.

For example, Linx is a low-code development tool to assist in moving large amounts of data, integrating systems and automating processes to avoid large elements of custom development or manual, repetitive work. Below is a screen shot of the Linx software.

The following commentary is typical from the players in the low-code vendor ecosystem:

“The AI uptake figures are very encouraging, but key barriers to execution remain in both the US and UK,” commented Gaurav Dhillon, CEO at SnapLogic. ”For organizations to accelerate their AI initiatives, they must upskill and recruit the right talent and invest in new technology and tools. Today’s self-service and low-code technologies can help bridge the gap, effectively democratizing AI and machine learning by getting these transformative capabilities into the hands of more workers at every skill level, thus moving the modern enterprise into the age of automation.”

Low-code Vendor Ecosystem

Rarely does a week pass these days without a new low-code vendor showing up on my radar.

Vendors like Salesforce have been working hard to bridge the data science skills gap by empowering Salesforce developers and admins with “point and click” solutions and low-code services in the Einstein platform. 

As another example, C3, a leading enterprise AI software provider for accelerating digital transformation, recently introduced the C3 Integrated Development Studio (IDS), a low-code/no-code environment for developing, deploying, and operating enterprise AI applications. IDS provides data ingestion, data modeling, machine-learning feature engineering and model lifecycle management, and a metadata-driven UI development tool. The hybrid, multi-cloud distributed architecture of C3 IDS enables secure, highly available, and rapidly scalable application development. C3 IDS delivers a developer experience through a low-code/no-code environment that accelerates developer velocity, an important capability for building complex enterprise-scale applications. The company claims that their customers have already built end-to-end applications for a wide range of use cases on C3 IDS, including predictive maintenance and yield optimization.

Some of the sentiment coming from hopeful enterprise IT leaders is absolutely glowing. Here’s a sample:

“Innovation can no longer only be driven by IT. The priorities of digital business require that BMC empowers faster innovation across organizations, so we are raising our commitment to developers and building an ecosystem where we support ‘no-code, low-code and pro-coder’ developer-environment capabilities,” said Nayaki Nayyar, president, Digital Service Management at BMC. “In a complex multi-source environment landscape, BMC Innovation Suite enables businesses to accelerate digital service management apps and services getting to market through agile app development and offers a huge competitive advantage to those companies adopting it.”

Here is a compelling visualization that encapsulates the low-code vendor ecosystem:

Low-code

Amazon recently announced its “Alexa Blueprints” program, which allow users to create their own personalized games, flashcards or pre-recorded information on Alexa devices. The question is whether this “low-code” tech is simple enough for end users. In short, no. While Amazon’s low-code push opens the door for many consumers to take control of their own devices, it still presents plenty of challenges. The offering requires basic coding experience (that most users don’t have), and takes a few hours to create one “skill.” Although some may view this solution as a step forward, the presence of any code at all will slow Blueprints’s progress. Amazon may try to eliminate code altogether and get Blueprints into the mainstream, but a fully no-code process designed to broaden its audience and impact will be fraught with problems.

Low-code: Substance or Hype?

My problem with low-code/no-code solutions is that this notion is nothing new. It’s a replay of past attempts at eliminating coding from the application development equation. There have been many false starts dating back to the 1980s, and they were all followed by “low-code/no-code winters” where coding once again reigned. 

There was a period when there were “automatic programming” tool-kits that offered point-and-click methods for designing and creating data entry forms and management reports. The tool would then generate the programming code to implement the business process the user designed visually. But invariable, a programmer would need to supplement the generated code with additional, custom code. These tools circulated for several years, but eventually faded away because people realized that programmers were still necessary.

About a decade later, early PC-based database systems evolved to include so-called “application generators” which essentially were no-code attempts to automate query, form and report creation. “AppGens” eventually fizzled because it became apparent that business requirements had too many special cases and complex requirements that automated tools simply could not handle without code. 

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I’m seeing the same hype cycle today with low-code/no-code that is reminiscent of the above attempts to eliminate coding. In my opinion, it’s just not going to happen, for the same reason why “AutoML” tools aren’t going to eliminate the data scientist. Programming is an art as much as it’s a science, and computers just don’t have the kind of creativity needed to listen to complex business requirements and come up with a software to implement these applications. I’m expecting to see yet another low-code/no-code winter in the next few years.

Daniel Gutierrez, ODSC

Daniel Gutierrez, ODSC

Daniel D. Gutierrez is a practicing data scientist who’s been working with data long before the field came in vogue. As a technology journalist, he enjoys keeping a pulse on this fast-paced industry. Daniel is also an educator having taught data science, machine learning and R classes at the university level. He has authored four computer industry books on database and data science technology, including his most recent title, “Machine Learning and Data Science: An Introduction to Statistical Learning Methods with R.” Daniel holds a BS in Mathematics and Computer Science from UCLA.

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