Founded in 2015 by Yaniv Avidan, Avner Atias and Gideon Barak, MinerEye is a Big ‘Dark’ Data Analytics Platform. It was created in order to enable automated governance focusing on unstructured data forms across disparate data stores such as distributed file shares, endpoint and cloud repositories. This found its roots in the thought that the most important data challenge for organizations is securing data and in particular, finding the key business critical sensitive data that needs protection. At the time of MinerEye’s inception, machine vision system was being used to track targets from drones, which naturally led to the idea that if machine vision can track moving objects over video, it can also track any data that is based on bytes.
“One of the best projects that MinerEye has undertaken involved one of the largest banks in Europe, where they managed to map and classify 15 Terabytes worth of data that was older than 3 years”
The team at MinerEye comprises of leading industry experts with vast worldwide experience in data protection and cyber security. Within a short tenure, the organization has managed to prove and bring value to dozens of companies from various verticals and information profiles. With businesses being more and more data focused, and with data being created and used at an exponentially faster pace every year, security officers often end up not trusting the traditional approaches to protect data. This in turn creates a bottle neck and slows down the business, and at times, even blocks it. Hence, the requirement to evaluate and consider automated security processes comes into prominence. This results in not only increased team efficiency and productivity, but also provides an immediate ROI while protecting the organization’s most important aspect – its sensitive data.
Data protection, as we all know, is a field that traditionally requires enormous service oriented efforts and resources. To complement this, MinerEye has developed a unique technology that minimizes these efforts by automating critical and continuous activities such as mapping and identifying key sensitive data. This way, every executive and data steward in a company can differentiate between public data and sensitive data, such as business models, processes, intellectual property, trade secrets, customers and employees private and protected info etc. MinerEye has really managed to stand out when compared to its competitors by bringing about the ability to automatically map and classify enormous amounts of unstructured data that is unmanaged and uncontained.
“VisionGrid enabled us to automatically and accurately classify both our legacy and day forward data for both data protection and compliance purposes with minimal effort”
-Director of Information Governance – diversified financial services company
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The VisionGrid platform was developed by MinerEye as a plug and play virtual box design that consists of an Ubuntu server, MinerEye proprietary algorithm software, ElasticSearch and PostgreSQL repositories, all packed into one VMware virtual machine. This can be deployed in multiple VM’s to scale up and down on demand, and implement internal physical segregation. By visualizing sensitive data clusters and their attributes, the system GUI enables users to tag the data and maintain an organized classification convention. At the same time, the backend focuses on continuous scanning, mapping and matching data to clusters, all while the machine’s learning module learns and maps the behaviour of the data. On September 2015, the Gartner-Maverick report announced that MinerEye had built a platform that enables continuous control over information assets while monitoring and alerting anomalous behaviour. For this, MinerEye has two patents pending in the USPTO and PCT.
The integration of VisionGrid with other security systems has enabled a substantial increase in system effectiveness, when it comes to data management and protection. One of the best projects that MinerEye has undertaken involved one of the largest banks in Europe, where they managed to map and classify 15 Terabytes worth of data that was older than 3 years. All of this was undertaken in just under three weeks.
In the upcoming days of business, MinerEye plans on enhancing their computing performance to outpace the Data Growth challenge, and become a one stop shop for companies to manage their sensitive data. This plan includes the stewardship of data for decision making by enhancing proactive reporting, auto-tagging capabilities and connecting to as many systems as possible.