Read more about author Neha Das. In today’s data-driven business environment, enterprises are increasingly relying on sophisticated data migration strategies to manage and move vast amounts of information, particularly unstructured data. As enterprise IT infrastructure evolves, so too does the complexity of data migration. The scale, speed, and accuracy required to successfully migrate large datasets – often containing billions of files – pose significant challenges. These unstructured data migrations, when done…

Read more about author Tejasvi Addagada. Data has evolved from a back-office function into a central driver of innovation, customer experience, and regulatory compliance. Yet, many organizations still apply a one-size-fits-all approach to data governance frameworks, using the same rules for every department, use case, and dataset.Here’s the issue: What works for managing a legacy HR system doesn’t work for a real-time fraud detection model. Governance journey needs to be…

Read more about author Rytis Ulys. A recent AI and Information Management report has shown that 64% of organizations manage at least 1 petabyte (PT) of data, and 41% manage at least 500 PTs. In itself, this is perfectly fine – data is the new oil, after all. The problem is, however, that anywhere between 40% and 90% of this data ocean remains dark, which is to say – neither analyzed nor used.  To…

Read more about author Itamar Ben-Hemo. Business insights are only as good as the accuracy of the data on which they are built. According to Gartner, data quality is important to organizations “in part because poor data quality costs organizations at least $12.9 million a year on average.” So, we believe that it stands to reason that providing access to the most recent data points across your enterprise is going…