IOTA Foundation has announced a collaboration with Dell Technologies with the focus to develop a tool to measure the authenticity of data.
The tool, called Alvarium, aims to help companies properly evaluate any acquired data before using them in applications.
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All businesses understand the importance of carrying out detailed projects and company assignments based on genuine data. But with Blockchain technology, data measurement and analysis can even be better, according to the Project Alvarium team.
The team stated that if data is manipulated and not properly utilized, it can result in lousy decision-making in companies.
The IOTA foundation is a decentralized network and open-source protocol dedicated to the Internet of Things (IoT). It’s not clear how this partnership will increase interest to buy IOTA (MIOTA) or whether the token’s price may be affected.
The project was launched initially in 2019
With Project Alvarium, data will be properly checked before apps start applying it, which makes sure there is lesser room for application errors. The project is targeting all apps that utilize large volumes of data. It hopes to ensure the data is safe to use.
Project Alvarium began in 2019 after the development of a similar project known as Data Confident Fabric (DCF). After the creation of DCF, it was remodeled using IOTA’s streams framework, adding the vital scalability and security to ensure trust in the data.
Project Alvarium will benefit large companies
Some large companies always find it difficult to deal with a large volume of data. Sometimes, they are not able to verify the authenticity of the data before use. Project Alvarium will enable the initial integration of companies’ software and hardware which needs a high level of supervision and compliance with high regulatory demands.
The team pointed at the global pandemic as a real-life situation where Alvarium could be very useful. The COVID-19 pandemic caused multiple lockdowns last year, and the team stated that Alvarium would have been used to ensure effective data management.
Businesses traditionally return to traditional methods when they are unable to trust their input data in decision-making systems.