Will a no-code environment hold up for metaverse data?

The volume of global data was already climbing rapidly, but preliminary metaverse statistics predict that it will contribute to a 20-fold increase in worldwide data usage by 2032. This new version of the World Wide Web will incorporate advanced technologies to increase users’ immersion, and will be an attempt to unify virtual and physical environments. All of this will require a far greater amount of data than is currently flowing through today’s web infrastructure.

Whether it’s sooner or later, the metaverse will inevitably arrive, in whatever form it may take. So how can companies handle metaverse data analytics effectively? And will they need to implement customized code to achieve this?

Increasing users = exponential data growth

We’ve seen leaps in online data usage before. The jump from Web 1.0 to Web 2.0 was large enough. The rise of video on social media then began forcing many platforms to handle larger data streams.

And during the pandemic, the rise of virtual events required yet more bandwidth. Instead of in-person gatherings, enterprises began sponsoring large group video conferences, offering delegates direct virtual access to speakers. Such events involve thousands of users in what could be considered a rudimentary metaverse environment.

This new leap into the metaverse will be an explosion of data volumes on a whole new scale. The presence of each user who enters this type of environment will generate large additional data streams. And already, 74% of US adults say they would use the metaverse.

So as we move from terabytes and petabytes – to exabytes and zettabytes – what resources do you need to unify your data reliably?

Big data strategies need a big data infrastructure

As with other technologies, the rise in popularity of immersive media presents an opportunity to reach your customers where they are, and introduce potential new revenue streams. But if you don’t plan ahead, these new data sources will soon become a liability rather than an asset. To keep up will surging data volumes, you need to consider the following:

1. Scalability

You need to understand the format of the new data sources and how to connect them with others in order to successfully scale your data ops. If you need to use multiple APIs for multiple different purposes, for instance, the process suddenly becomes highly complex. To deal with multiple data pipelines, you need an automated data integrity engine that can scale as the number of data sources increases.

2. Time to build

Strategic data assets also take time to build manually. For example, it can take up to a month to build a new data connector manually, and by that time the data from the source, such as Facebook or Snapchat, will be out of date. It’s no use having access to outdated information when you need to make informed business decisions based on current data. What’s needed is the flexibility to quickly add more data connectors to reach real-time or near-real-time data. This can be achieved using automation.

3. Smart data pipelines

As data volumes mushroom in size, it becomes increasingly important to streamline the amount of raw data extracted in the first place. For example, you may only need 10% of a 1 TB dataset for actionable data. Pulling the whole terabyte only to delete 90% of it would not only be a waste of computer processing, but also contribute to slower delivery of the final result. Instead, you need to use smart APIs that will selectively extract only the data that your team requires.

In short, all of these elements require automation. Otherwise, your engineering team will be burdened with a ton of manual coding before you can even start to connect these new sources. So in answer to the question “will a no-code environment hold up for metaverse data?”: Yes, it will. But only if you implement a powerful data automation platform that can handle data sets of this new magnitude – and you factor in time to build this new automated data ops infrastructure well before you need to process the data.

If you’re a data-driven company, it’s important to bear in mind that the metaverse, or immersive web, is merely a new set of data sources. While there’ll be more datasets to handle, the fundamental challenges will remain the same. Your solution should be robust in the face of anticipated technologies, but this need not require any additional customized code from your internal engineers.