Understanding the metaverse with data science

The interest in the metaverse concept makes it clear that this new concept can open up new possibilities for companies. Although the metaverse is still in its infancy, there are plenty of ideas for what it will eventually look like. One thing is for sure: this virtual world will produce a huge amount of data.

Companies already have to deal with a multitude of data sources that need to be processed and analyzed, and the number is only growing. The metaverse, also known as the next iteration of the internet, will put more of a spotlight on data scientists within an organization. It’s up to these teams to make sure they’re fully prepared to manage this explosion of data and extract actionable insights from it to drive business forward.

First steps

“D&G launched Collezione Genesi, a collection of NFTs that fetched approximately $5.6 million at auction”

Several brands have already taken their first steps in the metaverse, and there are also brands that are already trading non-fungible tokens (nfts; property type) in this virtual world. In collaboration with UNXD, an NFT marketplace for digital luxury, D&G launched Collezione Genesi, a collection of NFTs that fetched around €5 million at auction. D&G is an example of a brand that recognizes the value of the metaverse, and as a result, D&G has uncovered new insights into consumer behavior and purchasing patterns.

The metaverse has the potential to revolutionize the way industries operate and how we live our daily lives. It can provide innovations for customers, build stronger relationships with people around the world, and provide businesses with a new source of revenue. The possibilities are endless, but only if a company has the right infrastructure to take advantage of it.

High speed

Currently, many organizations do not have a strategy for maximizing their data science capabilities. This limits your ability to truly understand data about the company or its customers. The metaverse will continue to expand and innovate at a rapid rate. If organizations are not properly prepared, it will be almost impossible to catch up.

Therefore, data science teams need to ensure they have a data cloud platform that can collect and process internal and third-party data through a single point of access. This shortens the time needed to reach insights. This model must be able to process structured, semi-structured, and unstructured data, while breaking down data silos and bringing together actionable insights. This is the only way to learn from the amount of data the metaverse will provide.

Companies must also set up the right processes so data scientists don’t have to duplicate entire data sets. This reduces potential security or compliance issues while accurately tracking that only the correct users and applications have access to the data in question. We may not know exactly what to expect from the metaverse, but if companies have the right data cloud platform, they can be responsive and flexible in their approach.

lessons

“It’s important for data science teams to look at the metaverse with an open mind as an opportunity to improve the business”

Data science teams must now spend time reflecting on the shortcomings of the current strategy, such as data silos and an unmanageable number of data sources. They must then apply these lessons so that they can effectively prepare for the future. By looking at other recent innovations, such as blockchain and cryptocurrencies, and the regulatory challenges they faced, companies can learn a lot about the challenges ahead. We can expect to see regulation around the metaverse fairly soon to ensure that companies abide by the rules and process data correctly.

It’s important for data science teams to view the metaverse with an open mind as an opportunity to improve the business. With all the additional knowledge, they can better understand and serve their customers. While the metaverse has the power to boost connections, strengthen relationships, and expand businesses, this development will undoubtedly come with a huge learning curve for businesses. So now is the time for organizations to properly prepare for the metaverse and ensure their data science approach is simple, modern, and effective in making sense of this new world.

(The author Coen Bos is vice president of Northern Europe at Snowflake.)

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