everiToken TECHNICAL WHITEPAPER Version 3.0

whitePaper | August 2, 2022

The volume of data has exploded across all sectors in the last decade. Enterprise data has grown enormously, and organizations must contend with more unstructured data than ever. In fact, 95 percent of businesses cite the need to manage unstructured data as a challenge.

whitePaper | November 23, 2022

Artificial intelligence (AI) and machine learning (ML), along with data analytics, are widely seen as a way to tackle everything from daily inefficiencies and low productivity, to advancing healthcare and climate change mitigation. As more organisations look to leverage their data more effectively, demand for people with data capabilities is only going to grow

whitePaper | November 25, 2022

We live in a world of exponentially growing data. Within these massive datasets lies incredible potential, but only if users are equipped with tools capable of managing big data at scale and without lag.

whitePaper | November 26, 2019

Artificial intelligence (AI) is a rapidly growing field of technology with potentially significant implications for national security. As such, the U.S. Department of Defense (DOD) and other nations are developing AI applications for a range of military functions. AI research is underway in the fields of intelligence collection and analysis, logistics, cyber operations, information operations, command and control, and in a variety of semiautonomous and autonomous vehicles. Already, AI has been incorporated into military operations in Iraq and Syria. Congressional action has the potential to shape the technology’s development further, with budgetary and legislative decisions influencing the growth of military applications as well as the pace of their adoption.

whitePaper | September 1, 2022

Organizations often adopt a hybrid cloud strategy when deploying their first analytical solution to the cloud. The cloud combines sheer infinite scalability with consumption-based pricing. These are desirable attributes for analytical environments that require scalability and can be very expensive when scaled for maximum capacity over an extended period.

whitePaper | October 13, 2022

Generally, data-driven companies mainly struggle with data quality issues. Massive amounts of data, changing data storage requirements due to changing company regulations, and the various types of data sources and formats do make data management quite difficult for companies. Hence, the need for robust DataOps took to automate and simplify data life-cycle phases is of utmost importance at this point. Here are, some of the most important DataOps took that professionals can use in 2022.