Mito is low-code data analysis tool inspired by spreadsheets. When you edit the spreadsheet, Mito generates Python code directly into your Jupyter lab notebook.
The benefit here is that there's no lock in. If Mito support the action the user wants to take, they can use Mito for a quick point-and-click experience. If not, they can just write Python code as they normally do!
I agree that no-code is limited to some general scenario, but there're still a lot of them.
Thus, we decided to leave an opportunity to choose which way to go: use mouse for simple / general actions or use SQL console by power users to archive some complex results.
If you are an accomplished Python programmer, you might code a solution or (e.g. if you want to do something ad hoc quickly) use a no-code tool.
If you aren't a programmer, your choice is typically: learn Python, use Excel, wait for a programmer to do it for you or use a no-code tool. A no-code tool will often be by far the best solution.
TABLUM.IO simplifies data extraction/load/import from files, web and databases. You can load data from postgres, json file and application API, then merge data into a single table, display as a sheet and draw a chart for it. Wheres it is almost impossible with Excel or GoogleSheet.
We're running a low-code internal tool builder and everything is built / configured with code, but you never start from scratch, so it's 50x more productive then building your own.
Perhaps, depending on your definition of programmers, but lots of people can use logic. An accountant making complex calculations and forecasts in Excel is surely just as logic and precise as a programmer hacking something together in Python.
There’s a difference between being able to program (everyone) and being a professional programmer.
It’s like everyone can cook dinner but not all can be a chef. This doesn’t mean the solution is microwaveable meals for everyone.
I’ve tried many no code tools over the decades. As an individual and as a group.
Ease of use is really important. But I think easy for Python programmers is better than easy for people to click. Logic is logic, so whether you program in code or via some wack gui, you still need programmers.
Every time it’s come down to regretting committing to a closed, proprietary “programming language” that is the no code tool.
The exception is for simple stuff. But with data projects simple projects usually get complicated fast. So Id rather use a tool that scales well rather than one that starts easy but then is very hard to scale.