Sander Kerstens (Director Data Analytics at Vanderlande) on: data mesh, what it means and how Vanderlande has approached its implementation. Sander talks about the challenges they’ve faced and how they’ve addressed them. Listen to hear tips on how to tackle a data mesh implementation.
In a changing digital world, old business models are being disrupted and the winners will be those who can adapt quickly. We are in the transition from web 2 into web 3. Web 1, 2 or 3, it doesn’t really matter, because it is all data, right? Then pay attention because it is not that simple.
“it doesn’t really matter, because it is all data, right? “
Web 2 is company centric, with a need for data availability, quality and interoperability for monetization. Topics most companies struggle with. Web 3 is user centric, meaning users own and control (their) data, with the potential share, collaborate and monetize data.
The last decade, the focus was on web 2. You can recognize this in the high volume of cookies and apps to capture consumer data. The growth of central data platforms that store, harmonize and share data. And the rise of the function of data scientist.
How will the web 3 differ? Web3 is powered by a decentral network of peers that enable data sharing between users and applications. This allows for a more easy, transparent, and secure exchange of data. Exactly the struggles of web 2.
This data exchange is gaining traction in the mainstream, supported by the now acceleration increase of blockchain and on the horizon, the (meta)verse (The Metaverse: new frontier that re-imagines retail & health. And data re-imagines the Metaverse. – D8A directors). Decentral data sharing in web 3 allows users to interact directly without a central intermediary company. It also allows for an even faster growth of data, which will require adjustments in the analysis of data as well as an opportunity to increase development of AI solutions. And – important – it gives the user control where and how to share which data with who. In theory, the ultimate data privacy.
Web 3 does require rethinking data security, good to keep that top of mind.
Blockchain (or smart contracts) is a good example of how data provenance (what is the source of the data, initial data quality and which data processing activities have taken place. Provenance is important for companies and consumers alike) can be controlled. By capturing every step of the way in smart contracts, every step is retraceable. Relevant for companies, e.g. for fraud detection and prevention. Or being able to build a – decentral – large volume of scientific data, one of the key challenges today.
And for users, blockchain is relevant to understand how their data is used and if it is high in demand, thereby creating monetization possibilities for users. Increasing the incentive for data sharing. Decentralized data democratises data access, enabling companies AND users to create, deploy, and use specific instruments that were before restricted Here the shift from company-centric to user-centric becomes clear. Data can become your income.
Either in web 2 or 3, data is the foundational layer of innovation. Web 3 extends that with building meaningful relationships between companies and users (cut-out the middle men), improved quality of data, elevated possibilities and value of digital transactions and increased data privacy.
As a user, what do you need to have in place? Create a thorough understanding of your rights as owner of your own personal data. Share your data were and when you want, but act wisely. Understand which data can have value where and monetize accordingly. Have your data available in a personal data vault in accordance with Self Sovereign Identity principles. In short, become a data expert!.