No-code applications are expanding because users are frustrated with IT bottlenecks and they want to get their reports and apps faster. It’s also worth noting that most no-code reports involve analytics.
“The point is, businesses can’t take advantage of data science if they don’t understand it, and not everyone can hire a team of data scientists who clock in six-figure-plus salaries in the U.S.,” said Frederik Bussler, an AutoML and no-code enthusiast. “All leaders should be empowered to use data science, without needing (to be) an ‘AI wizard’ or ‘code ninja.’
“That’s what it means to democratize data science. The goal of no-code tools … is to make everyone a data scientist, letting teams of all sizes and skill levels take advantage of this technology, from visualization to predictive analytics.”
How does no code work?
By automatically generating code that works with an organization’s software and hardware—but that is not optimized for any particular company IT environment—no-code application and report generation engines can produce work rapidly for non-programming personnel in business departments. The trade-off is that the code generated is not always the most efficient in its use of IT resources because of its generic nature. As a result, the auto-generated code from no-code tools will likely consist of more lines of code than would be written by an experienced IT developer who’s familiar with the company’s operating systems and hardware. This excess auto-generated code can require more processing and often more storage per application, and it can waste IT resources, such as storage and processing, as a consequence.
This is where the old school enters into it, because old school IT looks at the economics of the processing and storage being consumed and weighs it against the value of the data and information being used.
What the old school says
In its economical approach to processing and storage, old school IT uses the 80:20 rule when it evaluates items like reports. In other words, for every 100 reports you produce, 20 reports are typically widely used and the other 80 are either seldom used or not used at all.
IT best practices for report maintenance have been founded on the 80:20 principle for decades. You see these practices in play today when IT purges reports that haven’t been used for x length of time, with the time frames for non-use being established and agreed to by IT and business users. In this way, storage and processing resources are preserved for new uses and the cost of unused or underutilized resources is reduced.
How the 80:20 rule should be applied to no-code analytics reports
In a July 2021 survey of 414 IT and business professionals, TechRepublic Premium revealed that nearly half (47%) of those surveyed currently use low-code or no-code tools in their organizations. And of the 35% who weren’t using low-code or no-code, one in five (20%) said they intended to adopt the technology in the next 12 months.
The data suggests that an enormous amount of no-code reports will be produced, with most being generated by individual user departments that have their own citizen developers.
This is the time for companies to enact policies for the deluge of low-code reports that must be managed, and there is no reason to believe that the 80:20 rule won’t apply to no-code reports in the same way that it has applied to other forms of reports. Consequently, it makes sense for both IT and end users to establish rules for monitoring report usage for no-code applications, to determine end-of-life non-use time frames and to eliminate those no-code reports that haven’t been used for a significant period of time.
SEE: Electronic Data Disposal Policy (TechRepublic Premium)
But here’s the catch: Who does this? Will IT, which has functioned as the central governing agency for report reviews in the past, be aware of the troves of no-code reports that end users might have stored out on clouds? This is where it makes sense for companies to create guidelines that govern the lifespans of no-code applications, systematically retiring those that have lost their usefulness and thereby conserving cloud and/or in-house IT resources and spend. In the process, IT and end user should work together.
The goal with no-code should be as it is for any type of coded report: a report and/or app should be eliminated if it isn’t used over a defined period of time.
Companies that ensure that the 80:20 rule is universally applied to all analytics reports—be they standard, low-code or no-code—position themselves to ensure that IT resources are only consumed when they deliver value.