Archival data is piling up faster than ever as organizations are quickly learning the value of analyzing vast amounts of previously untapped digital data. Industry studies consistently find that the vast majority of all digital data is rarely, if ever, accessed again after it is stored. However, this is changing now with the emergence of big data analytics made possible by Machine Learning (ML) and Artificial Intelligence (AI) tools that bring data back to life and tap its enormous value for improved efficiency and competitive advantage.
The need to securely store, search for, retrieve and analyze massive volumes of archival content is fueling new and more effective advancements in archive solutions. These trends are further compounded as an increasing number of businesses are approaching hyperscale levels with significant archival capacity requirements.