No-Code
Lucille Crombez

21 mai 2021

Big Code: The New Challenge of AI

Big Code is often compared to Big Data, for they both are challenging for businesses. Big Data is defined by Gartner as “high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.” Thus, Big Data is a challenge as it requires a lot of work from companies in order to control it. 

Now, what about Big Code? What does it mean and why is it a struggle?

What does it consist of?

The whole concept of Big Code came to light with the 2020 survey conducted by Dimensional Research. It essentially refers to the fact that volumes, quantities of code are constantly increasing and becoming more complex. 

The survey mentions the 4Vs used to define Big Data and how they actually also apply to discuss Big Code. 

Big Data

(Source: WAC)

While the 4Vs referring to Big Code are exactly the same, the attributes conferred to them by the survey (p. 1) are more detailed and differ slightly:

  • Volume: exponential increases in the amount of code
  • Variety: increased complexity in the languages, tools and processes used for delivering software
  • Velocity: accelerated delivery cycles that mean code is changing faster and being shipped virtually every day
  • Value: the reimagination of business models and practices through high-quantity software.

Now that you have a clearer understanding of what Big Code is, let us take a look at the challenges it brings.

Big Code: why is it disruptive?

When the 500 businesses taking part in the survey were asked whether or not Big Code was negatively affecting their work, here were the answers they gave:

Is your organisation affected by Big Code

(Source: Dimensional Research/Sourcegraph)

But why do they perceive it as a challenge? 

The first issue is that with this immense amount of code, it is much harder to identify the potential glitches or problems that might occur. Equally problematic is the fact that this much information is difficult to take in and thus makes it harder for employees to figure out how to deal with Big Code and significantly impacts the probability to meet the company’s quality standards. 

A third issue raised by the survey is the lack of appropriate tools to face Big Code. Indeed, while these increases have been particularly important, the required updates were not put in place thus adding to the struggles of the employees and the companies and making their tasks counter-productive. 

What are the solutions?

One of the solutions would obviously be to provide new, efficient tools so as to make sure employees and companies as a whole can manage Big Code and still deliver great performances and results. The survey reveals that the problem is mainly due to the fact that the management is not conscious of the needs of the developers. Thus, executives should get better acquainted with what it is their developers need so as to provide them better tools which will enable them to improve their efficiency.

The other step that could be taken is to ensure that your team as well as your company are developing strategies to make it more manageable, by thinking about the resources that could be useful and valuable.

Ultimately, to make the challenge of Big Code less unbearable, the main step forward would be to diminish the amount of code you are dealing with by deleting the code you hardly use from your codebase.

2OS: No-code as a way to avoid Big Code

2OS is a no-code platform, thus you will not be subjected to the problems and challenges that Big Code implies. 

The 2OS platform enables you to create your own no-code app while using technologies such as AI, analytical tools, etc. It also provides your business scalability and the opportunity to extend its use from a single individual to the entire company. 2OS can respond to any demand whether it be focusing on financial AI, document analysis, etc.

2OS also gives you algorithms with which you can analyse your documents and data so as to extract useful information with strong value-added (DocReader for instance).

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