Combining the internet of things (IoT) with automation is essential if you want to remain competitive while continuing to streamline your processes.
That’s because, without the data the IoT provides, you can miss the critical insights you need to stay competitive. And without automation, you’re stuck sitting through a growing mound of data that can leave you in a worse position.
The solution is for businesses to integrate IoT development platforms with workflows using low-code.
How Much Data Can The IoT Collect?
In 2019, the estimated volume of data in zettabytes (a trillion gigabytes) from the IoT was 13.6. In 2025, it’s estimated to be 79.4.
The average data companies manage, however, can vary. Usually, it’s anywhere from 47.81 terabytes (TB) for the average small business to 347.56TB for the average enterprise.
In short, the IoT can provide a business with a lot more data—no matter your business’ size. This opens the door to deeper, more accurate customer and business insights. (Also read: 6 No-Code AI Platforms That Are Accessible to SMBs.)
However, the sudden surge of all that extra data also presents a major challenge.
The Challenge With Implementing IoT Networks
The IoT empowers organizations to increase productivity, streamline workflows and redefine how a business operates. The data streams it provides can move across a range of IT infrastructures. Innovation is essentially constant, with new apps and features added daily.
When you start connecting more and more devices on the IoT, you face an extensive data lake with streams flowing into it constantly. Thus, the challenge quickly shifts from capturing data to managing data. And that can create a major bottleneck for growing businesses.
When people try to explain the benefits of the IoT, they often use the logistics metaphor: Sensors in refrigeration containers can track temperatures to ensure perishable goods stay within defined parameters.
It’s a great example; but what happens if you want to analyze more than just the temperature of storage containers? What if you, for example, want to track how efficient your vendors are by measuring a range of data across your entire supply chain? All of a sudden, you’re facing data overload. (Also read: IIoT vs IoT: The Bigger Risks of the Industrial Internet of Things.)
Collecting data from various sources and combining that information into a clear picture can be challenging—especially if you’re trying to do this manually.
More Data, More Problems?
Often one of the biggest pushbacks to connecting more systems into the IoT is whether anyone has the time to actually analyze that data.
Depending on how you approach implementing IoT, it can be like turning on a firehose of data. And if you don’t have the right systems, that data ends up where most data goes to die: endless spreadsheets.
When data is siloed in spreadsheets (or other platforms), it becomes difficult to manage. Reporting can’t happen in real-time. Manual data entry errors are costly and put your business at increased risk. Moving data around requires either delegating it to a team member (who has to find time to do it) or outsourcing. Both involve more costs. (Also read: Destroying Silos With Integrated Data Analytics Platforms.)
Either way, it can be a risky investment for growing businesses with limited IT resources.
Alternatively, you can build out custom applications that connect these systems with a central database. But this creates problems as well: Custom application design is expensive, time-consuming and potentially risky from an ROI perspective.
And if you’re trying to transform your business processes to stay competitive, your IT budget and department are probably limited on time and resources.
How Can IoT Networks and Low-Code Support Business Functions?
Low-code platforms are Software as a Service (SaaS) interfaces designed to streamline the development of applications and integrations. In short, they’re an incredibly agile way to build apps. Rather than building up complex custom applications from scratch, you simply drag and drop bits of code or visual elements to create the solutions you need. (Also read: Is No-Code Development About to Go Mainstream?)
This drastically reduces the time and cost needed to build custom applications. Instead of spending seven figures on custom app development and waiting months to test and go live, you can design custom software solutions in days.
Low-code platforms also present many benefits as a cost reduction strategy. As a SaaS platform, costs scale with use—which makes them very affordable solutions for businesses with a limited IT budget. Plus, they’re designed for people who do not have a coding background. This means they’re easier to use and onboarding is much faster (and cheaper).
Using low-code, you can quickly connect various IoT technologies to your existing business infrastructure. And you can consolidate your data into a single platform. In short, you’ll exchange data silos for actionable insights in clear data dashboards.
Additionally, these cloud-based platforms are more secure than many solutions businesses use to house data.
As an added benefit, several low-code platforms already have IoT support built into their framework. In the end, you can connect your technology faster. (Also read: How the IoT is Promoting Growth in the Micro Data Center.)
How Low-Code Reduces IT Backlog
Despite the benefits technological advances bring businesses, IT departments continue to struggle to meet business goals. IT backlog is a real concern.
As a result, connecting applications to the IoT in a meaningful way can be a real challenge for IT teams who are already bogged down with what seems like an endless list of open tickets.
IT professionals have to deal with maintaining dated operational technology, working within the limitations of current legacy systems and the debt that devours IT budgets. Moreover, they’re now dealing with increasing pressure to integrate systems and automate workflows—all of which requires a time and resource investment in better systems.
The strain is real and measurable.
Low-code empowers IT developers to work faster and more cost-effectively. Rather than build custom integrations to connect a hodgepodge of technologies, your IT department can rapidly build connections between new tech and your organization’s software architecture. The end result is a significant reduction in ticket backlog and more time for other projects. (Also read: Low-Code Platforms: The Solution to the Developer Shortage?)
Challenges with IoT Networks and Low-Code
While many of the mainstream low-code applications are built to support the IoT, there are still potential challenges.
For one, the IoT is complex. And even though users can build custom applications with only a little background knowledge in code, that doesn’t mean it’s necessarily easy to do so. You’re potentially looking at an intricate web of disparate systems, IoT endpoints and platforms. Plus, you need to know the best way to organize data streams and present them in meaningful ways. (Also read: Top 5 Ways to Organize the Data You Need.)
Additionally, applications are more complex: Advancements happen every day. IT teams, with their background in code, are better equipped to set up the necessary infrastructure businesses need to gain meaningful insights from these new technologies.
As a result, low-code isn’t positioned to replace software developers. Instead, it’s a tool that can help them scale their efforts. Other team members can write the basic business logic needed to run the automations and they can highlight the relevant data points. However, they still need to collaborate with IT to build the necessary infrastructure to support IoT effectively.
Despite the challenges it comes with, low-code platforms have the power to amplify the work developers do. And in the end, it can help them build the systems businesses need to capitalize on all the benefits the IoT and automation offer.
It’s important for businesses—especially those thinking the IoT is out-of-reach due to data complexities—to realize low-code is the ladder that will help grasp its full potential. (Also read: How Low-Code Development Will Bring Data Science to the Masses.)