Of course, there are some limitations to what you can do with no-code platforms. They’re not quite as flexible as traditional development environments, so if you want to do something truly unique or complex, you’ll likely need to hire a developer to do it for you. But for most people, no-code platforms are more than sufficient for their needs.
Have you ever heard of Microsoft Query?
Microsoft Query (in several forms) still exists and is still in use today. It’s the living embodiment of the infamous definition of madness oft (wrongly) attributed to Einstein that it’s doing the same thing over and over, and expecting different results.
There’s a reason people keep doing the same thing, even though it doesn’t give the intended results. Some strategies just look so much like they will solve the problem that it’s almost impossible to believe that they don’t. So people prefer to disbelieve the results than believe the solution can’t work. This isn’t insanity. It’s a perfectly sensible feature of inductive reasoning which is that the more times you try, the more likely you are to get the result you want. You’d be insane to argue with that. So you have to do quite a difficult (for many people, it seems) piece of reasoning: separate strategies and techniques susceptible to improvement by practice from those that are not.
Of course, in the case of Microsoft Query, there’s a powerful economic motivator.
People want to believe that you can carry out analytical operations on data without having to use computer code.
The idea of this is just sufficiently removed from simple repetition of the same failed strategy that many people will never realise that they are repeating the same action expecting different results.
The idea is that it’s easier to define complex relationships between data structures visually than verbally.
The theory being that drawing lines between visual representations of tables is easier than writing the words of an SQL statement.
People who don’t routinely work with data genuinely think that the choice is between the visual and the verbal, and they imagine that data analysts visualize data, so it must surely be easier to represent those visualizations directly, right?
The problem is that although we often call it a visualization, when you are imagining a data structure…
… okay. This is going to get weird but come with me on it.
The set of all integers is a one-dimensional space.
Add a dimension and you get a graph with coordinates that we normally represent as two numbers. Those two numbers give a location on a flat plane. So you can plot points on a graph, and maybe join them up with your choice of line of best fit.
Add a dimension and you get 3D. You can still just about represent that as an image, if you have a good understanding of the mammalian visual system. You know about perspective, right?
So what if you need a fourth dimension?
Coordinates in 1 dimensional space are expressed like this: 5
Coordinates in 2 dimensional space like this: 2,5
Coordinates in 3 dimensional space like this: 1,2,5
… and if you’re with me so far, you’ll know that the first two numbers refer to locations horizontally, and the third vertically. 3D printers, CAD programs, Blender, 3 point geometry, vectors in three dimensional space, etc.
All this can be represented by images that look meaningful to the human visual system, which is handy, because that’s what they are for.
But typical data structures can have dozens of dimensions.
Even the simplest ones usually have more than 4. Consider the database that underlies every Enterprise Management System. It has tables for products, clients and orders. You’ve already used up 3 dimensions right there. Supposing you need to create a proposal that demonstrates your ability to provide a subset of your product range to multiple client locations, taking account of vendor and resource availability and seasonal variations? That sort of thing is child’s play compared with evaluating the data from a clinical trial to determine if a new medical device is safe and effective, yet you’re already working with a minimum of five dimensions.
So sure, when thinking about data structures, we frequently “visualize” them, but not as cute 2d images that seem like 3d images “projected inside your mind.” Visualizing data structures so you can design queries for complex datasets is sometimes so difficult it has to be done iteratively. Processing time becomes a factor of query design. You can finish up with a sequence of queries, each of which is multi-dimensional.
Often, the only way to describe them is through the SQL statements that represent them. There will NEVER be a way of representing that as images, because the best that images can ever do is be 2 dimensions that fool your visual system into thinking there are 3 dimensions of space and one of time.
Microsoft Query persists because there will always be people who wishfully think that they can learn to analyse data without learning the “texty part;” without learning to process data (these days, mostly with Python it seems) and without learning to query data with SQL.
No-Code and low-code are wishful thinking except when they are teaching aids (as such, I will admit, they can be a good early stepping stone).
So no, no-code will manacle you, and you’ll love your manacles right up until you need to reach for the door handle.
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