Adrian Knapp | Source | Founder & CEO at Aparavi

Managing data has never been so important for organizations as more data is being produced by businesses than ever, and many of them are unaware that this data is costing them millions of dollars and putting their cybersecurity at risk. Businesses mistakenly feel that keeping all of their data will reduce risks, but the opposite is true. The likelihood of being the target of a cyberattack increases with the amount of unaccounted-for data a company has.

Understanding what data you have is an effective business strategy. Companies can do this by implementing effective data management strategies that identify redundant, outdated, and trivial data, also known as ROT data. Unaccounted-for data takes up space on servers and slows down processes. Companies buy disk after disk to support data growth, but come five years from now, they will run out of space and will have accumulated an abundance of disks. This process is unsustainable, increases security risks, and can cost companies millions.

A data assessment is a smart business practice because it helps companies scan entire file systems and takes a deep dive into the data ecosystem. The assessment can also read the data in unstructured files and reveal content. When you understand your data, you are in control to mitigate risk, reduce costs, and create value for your organization with confidence.

One of the first steps companies should consider is understanding their unstructured data to improve their data security. When you identify your data footprint, understand what you have and where it’s stored, you can make educated decisions on how to protect it, leading to an effective zero-trust environment. You can’t protect data effectively if you don’t know what you have or where it’s stored.

Enterprises of all sizes struggle under large unstructured data and are challenged to find, and identify the relevance, importance, and value of their information. With this strategic relationship Modus customers are now able to immediately reduce data risk, management costs, complexity, and reduce human error with automated data governance and compliance, even exploit their data for data analytics and machine learning.