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Joel Spolsky’s once prolific blogging output dried up years ago, but Things You Should Never Do, Part I is still a classic after 22 years. He wrote it as an outsider’s postmortem following the first beta release (6) of Netscape’s browser, three years after the previous major release 4. There never was a version 5. The team had decided on a full rewrite, and the resulting delay probably cost them their competitive advantage over Microsoft’s Internet Explorer.
“If Netscape actually had some adult supervision with software industry experience, they might not have shot themselves in the foot so badly”, he closes.
Much like running up bills on your credit card, technical debt can easily get out of hand. To avoid this happening, you need to keep track of how much debt you’re building up.
Technical debt metrics are designed to help you make sense of all the data you collect. There are many different metrics to choose from nowadays, and plenty of tools for recording the data.
In most cases, you aren’t the only person working on the same project or codebase. That means that other people get to read your code and have to understand it. That’s also true for the code comments you leave behind. Developers often write ‘quick and dirty’ comments without much context, leaving other developers clueless about what you’re trying to say. It’s a bad practice that creates only more confusion than clarifies things.
So, yes – you should be bothered with writing meaningful code comments to help other developers. A code comment that describes the function, the reasoning behind the function, and its input and output will speed up the learning process of other developers. Especially for junior developers, this information comes in handy when learning the code.
Gartner predicts that by 2023, over 50% of medium to large enterprises will have adopted a Low-code/No-code application as part of their platform development.
The proliferation of Low-code/No-code tooling can be partially attributed to the COVID-19 pandemic, which has put pressure on businesses around the world to rapidly implement digital solutions. However, adoption of these tools — while indeed accelerated by the pandemic — would have occurred either way.
Even before the pandemic, the largest, richest companies had already formed an oligopsony around the best tech talent and most advanced development tools. Low-Code/No-code, therefore, is an attractive solution for small and mid-sized organizations to level the playing field, and it does so by giving these smaller players the power to do more with their existing resources.
While these benefits are often realized in the short term, the long-term effect of these tools is often shockingly different. The promise of faster and cheaper delivery is the catch — or lure — inside this organizational mousetrap, whereas backlogs, vendor contracts, technical debts, and constant updates are the hammer.
So, what exactly is the No-Code trap, and how can we avoid it?
What is a No-Code Tool?
First, let’s make sure we clear up any confusion regarding naming. So far I have referred Low-Code and No-Code as if they were one term. It’s certainly easy to confuse them — even large analyst firms seem to have a hard time differentiating between the two — and in the broader context of this article, both can lead to the same set of development pitfalls.
Under the magnifying glass, however, there are lots of small details and capabilities that differentiate Low-code and No-code solutions. Most of them aren’t apparent at the UI level, leading to much of the confusion between where the two come from.
In this section, I will spend a little bit of time exploring the important differences between those two, but only to show that when it comes to the central premise of this article they are virtually equivalent.
Low-Code vs. No-Code Tools
The goal behind Low-Code is to minimize the amount of coding necessary for complex tasks through a visual interface (such as Drag ‘N’ Drop) that integrates existing blocks of code into a workflow.
Skilled professionals have the potential to work smarter and faster with Low-Code tools because repetitive coding or duplicating work is streamlined. Through this, they can spend less time on the 80% of work that builds the foundation and focuses more on optimizing the 20% that makes it different. It, therefore, takes on the role of an entry-level employee doing the grunt work for more senior developers/engineers.
No-Code has a very similar look and feel to Low-Code, but is different in one very important dimension. Where Low-Code is meant to optimize the productivity of developers or engineers that already know how to code (even if just a little), No-Code is built for business and product managers that may not know any actual programming languages. It is meant to equip non-technical workers with the tools they need to create applications without formal development training.
No-Code applications need to be self-contained and everything the No-Code vendor thinks the user may need is already built into the tool.
As a result, No-Code applications create a lot of restrictions for the long-term in exchange for quick results in the short-term. This is a great example of a ‘deliberate-prudent’ scenario in the context of the Technical Debt Quadrant, but more on this later.
Advantages of No-Code Solutions
The appeal of both Low-Code and No-Code is pretty obvious. By removing code organizations can remove those that write it — developers — because they are expensive, in short supply, and fundamentally don’t produce things quickly.
The benefits of these two forms of applications in their best forms can be pretty substantial:
- Resources: Human Capital is becoming increasingly scarce — and therefore expensive. This can stop a lot of ambitious projects dead in their tracks. Low-Code and No-Code tools minimize the amount of specialized technical skills needed to get an application of the ground, which means things can get done more quickly and at a lower cost.
- Low Risk/High ROI: Security processes, data integrations, and cross-platform support are all built into Low-Code and No-Code tools, meaning less risk and more time to focus on your business goals.
- Moving to Production: Similarly, for both types of tools a single click is all it takes to send or deploy a model or application you built to production.
Looking at these advantages, it is no wonder that both Low-Code and No-Code have been taking industries by storm recently. While being distinctly different in terms of users, they serve the same goal — that is to say, faster, safer and cheaper deployment. Given these similarities, both terms will be grouped together under the ‘No-Code’ term for the rest of this article unless otherwise specified.
List of No-Code Data Tools
So far, we have covered the applications of No-Code in a very general way, but for the rest of this article, I would like to focus on data modeling. No-Code tools are prevalent in software development, but have also, in particular, started to take hold in this space, and some applications even claim to be an alternative to SQL and other querying languages (crazy, right?!). My reasons for focusing on this are two-fold:
Firstly, there is a lot of existing analysis around this problem for software development and very little for data modeling. Secondly, this is also the area in which I have the most expertise.
Now let’s take a look at some of the vendors that provide No-Code solutions in this space. These in no way constitute a complete list and are, for the most part, not exclusively built for data modeling.
1. No-Code Data Modeling in Power BI
Power BI was created by Microsoft and aims to provide interactive visualizations and business intelligence capabilities to all types of business users. Their simple interface is meant to allow end-users to create their own reports and dashboards through a number of features, including data mapping, transformation, and visualization through dashboards. Power BI does support some R coding capabilities for visualization, but when it comes to data modeling, it is a true No-Code tool.
2. Alteryx as a Low-Code Alternative
Alteryx is meant to make advanced analytics accessible to any data worker. To achieve this, it offers several data analytics solutions. Alteryx specializes in self-service analytics with an intuitive UI. Their offerings can be used as Extract, Transform, Load (ETL) Tools within their own framework. Alteryx allows data workers to organize their data pipelines through their custom features and SQL code blocks. As such, they are easily identified as a Low-Code solution.
3. Is Tableau a No-Code Data Modeling Solution?
Tableau is a visual analytics platform and a direct competitor to Power BI. They were recently acquired by Salesforce which is now hoping to ‘transform the way we use data to solve problems—empowering people and organizations to make the most of their data.’ It is also a pretty obvious No-Code platform that is supposed to appeal to all types of end-users. As of now, it offers fewer tools for data modeling than Power BI, but that is likely to change in the future.
4. Looker is a No-Code Alternative to SQL
Looker is a business intelligence software and big data analytics platform that promises to help you explore, analyze, and share real-time business analytics easily. Very much in line with Tableau and Power BI, it aims to make non-technical end-users proficient in a variety of data tasks such as transformation, modeling, and visualization.
You might be wondering why I am including so many BI/Visualization platforms when talking about potential alternatives to SQL. After all, these tools are only set up to address an organization’s reporting needs, which constitute only one of the use cases for data queries and SQL. This is certainly a valid point, so allow me to clarify my reasoning a bit more.
While it is true that reporting is only one of many potential uses for SQL, it is nevertheless an extremely important one. There is a good reason why there are so many No-Code BI tools in the market—to address heightening demand from enterprises around the world — and therefore, it is worth taking a closer look at their almost inevitable shortcomings.
Organizations are continuously looking for ways to track, measure, and evaluate developer workflows. Done effectively, this creates the means to improve performance and code quality, reduce time to market and increase profits. But it’s not always easy to measure efficiency. What may first appear to be evidence of a team’s hard work may be an indication of the bigger challenges and inefficiencies of code churn.
What Is Code Churn?
Code churn is a measure or indication of how often a file changes. It typically refers to how often a developer throws out code (such as a function, file, or class) within the first 2-3 weeks of writing.
Last week we hosted a webinar where Alex Omeyer interviewed Adam Tornhill about technical debt: what is it, why it’s important, and how to manage it effectively. For this article, we’ve chosen some of the most interesting questions we’ve got from the audience. If you’re curious to learn more — check out the full version of the webinar.
Alex: I’m Alex, the Co‑founder, and CEO of Stepsize. I spend all of my time talking about technical debt with Engineering team members, and I’m genuinely pumped to have Adam, CTO and Founder of CodeScene, with me today.
If you’ve read our piece about the habits engineers need to beat tech debt, you might recall Conway’s law, which states that organizations which design systems […] are constrained to produce designs that are copies of the communication structures of these organizations.
It’s one of the forces that can push us towards technical bankruptcy because the systems designed by software engineers are constrained by their company’s organizational structure, over which they have little control. The right way to fight these forces is to talk about tech debt across the whole company so that everyone can understand why it’s vital to manage it carefully.
Introduction
Rails version 1.0 is approaching its 15 year anniversary, and there’s reason to celebrate the framework’s progress.
There have been hundreds of amazing products built with Rails since its creation.
The real problem is this: Why should you care about how much a delayed release costs you? Maybe you have a “sweet spot” in the way you start your projects or release them. “It just takes that long here.” (That’s the sign of a system impediment.)
Now, let’s try to calculate that cost of delay.
