Periodic Reporting for period 2 - Data TrackerTM (DataTrackerTM – Artificial Intelligence Enabling a Secure and Compliant Cloud Adoption)
Periodo di rendicontazione: 2020-04-01 al 2021-03-31
Identifying personal information in unstructured data, categorizing it, and tracking it to comply with the new GDPR regulation, is one of the utmost urgent and complicated subjects for European and multi-national companies today. However, companies are failing in achieving this today, as they are not in control of unstructured and cannot meaningfully identify all the data they produce. This becomes even more challenging while migrating data to the cloud: as companies are required to understand where sensitive data resides in order to comply with regulations.
The GDPR regulation is designed to unify data privacy requirements across the European Union (EU). A company that processes information of EU Data Subjects – which include end-users, customers and employees – must learn how to address its key requirements. Infringements can lead to fines of up to 20 million euros or 4% of the total worldwide annual turnover of the preceding fiscal year - whichever is higher. 92% of US multinationals surveyed by PwC named GDPR as a top priority, and 77% plan to spend $1 million or more on compliance.
This product vision dictates the focus on scale, and robust API and microservices architecture to support flexible deployment, large scale (Petabytes) and variant data sources, across enterprise-class companies. The product must support Channels, and SI partners to provide services with and up-sale on the integration service they provide.
The GDPR regulation is designed to unify data privacy requirements across the European Union (EU). A company that processes information of EU Data Subjects – which include end-users, customers and employees – must learn how to address its key requirements. Infringements can lead to fines of up to 20 million euros or 4% of the total worldwide annual turnover of the preceding fiscal year - whichever is higher. 92% of US multinationals surveyed by PwC named GDPR as a top priority, and 77% plan to spend $1 million or more on compliance.
This product vision dictates the focus on scale, and robust API and microservices architecture to support flexible deployment, large scale (Petabytes) and variant data sources, across enterprise-class companies. The product must support Channels, and SI partners to provide services with and up-sale on the integration service they provide.
The plan consists of five work packages that have seven milestones which include two major software versions development - V2.3 and V3.0. Currently (April 2021) the status of the project is completed according to plan, we've released to manufacturing (RTM) V3.0 as planned.
V2.3 Development (WP2 / MS4) - completed:
1) System requirements - collected (D2.1).
2) System Architecture and Design documents - completed (D2.2 D2.3).
3) Software development, System & Integration tests, System releases - completed (D2.4 D2.5 D2.6 D2.7).
V3.0 Development (WP3 / MS5) - in progress:
1) System requirements - collected (D3.1).
2) System Architecture and Design documents completed (D3.2 D3.3) - completed.
Maintenance & support (WP4) - completed:
1) Tuning & optimizations - We have defined and structured a learning process to collect system performance and feedback from the R&D to optimize and tune the ML models and system scalability. This process is run and maintained by our Customer Success manager on a daily basis (D4.1).
2) Customer & Channel support - We have an operational support process in place for production customers through our Customer Success Manager. Support is provided from remote according to pre-defined scripts, system security and vulnerability audits, and online training sessions for system owners and IT staff (D4.2).
Marketing, Sales, Sales Support, Customer acquisition (WP5) - completed:
1) Go-to-market plan and business model - completed. We have identified over 80 US-based Microsoft EMS potential partners and several direct customers through these partners (D5.1).
2) Marketing and communication plan (D5.2) Marketing collateral development (D5.3) - completed. Based on the GTM analysis, we have identified the gap in mid-market Microsoft O365 customers and focus on our communication channels accordingly.
3) Communication and PR execution - completed. We have positioned MinerEye as a leading security player for automated data classification services for enterprises. Build strong awareness for MinerEye with targeted analysts, industry thought leaders, and media and leveraged social media and lead generation platforms to achieve customer acquisition goals (D5.4).
4) Channel & partner training program development - completed. A partner training program has been developed by our Customer Success Manager (D5.5).
5) Channel partners training execution - completed. We have developed and executed a training plan for 32 signed channel partners worldwide (D5.6).
V2.3 Development (WP2 / MS4) - completed:
1) System requirements - collected (D2.1).
2) System Architecture and Design documents - completed (D2.2 D2.3).
3) Software development, System & Integration tests, System releases - completed (D2.4 D2.5 D2.6 D2.7).
V3.0 Development (WP3 / MS5) - in progress:
1) System requirements - collected (D3.1).
2) System Architecture and Design documents completed (D3.2 D3.3) - completed.
Maintenance & support (WP4) - completed:
1) Tuning & optimizations - We have defined and structured a learning process to collect system performance and feedback from the R&D to optimize and tune the ML models and system scalability. This process is run and maintained by our Customer Success manager on a daily basis (D4.1).
2) Customer & Channel support - We have an operational support process in place for production customers through our Customer Success Manager. Support is provided from remote according to pre-defined scripts, system security and vulnerability audits, and online training sessions for system owners and IT staff (D4.2).
Marketing, Sales, Sales Support, Customer acquisition (WP5) - completed:
1) Go-to-market plan and business model - completed. We have identified over 80 US-based Microsoft EMS potential partners and several direct customers through these partners (D5.1).
2) Marketing and communication plan (D5.2) Marketing collateral development (D5.3) - completed. Based on the GTM analysis, we have identified the gap in mid-market Microsoft O365 customers and focus on our communication channels accordingly.
3) Communication and PR execution - completed. We have positioned MinerEye as a leading security player for automated data classification services for enterprises. Build strong awareness for MinerEye with targeted analysts, industry thought leaders, and media and leveraged social media and lead generation platforms to achieve customer acquisition goals (D5.4).
4) Channel & partner training program development - completed. A partner training program has been developed by our Customer Success Manager (D5.5).
5) Channel partners training execution - completed. We have developed and executed a training plan for 32 signed channel partners worldwide (D5.6).
"1) United States Patent No. 10,372,731 was granted: “Method Of Generating A Data Object Identifier And System Thereof” in the name of MinerEye Ltd.
Filing Date: November 23, 2016
Filing No: 15/360,612
Issue Date: August 6, 2019
Patent No.: 10,372,731
Patent Term: 20 years from the filing date
2) United States Patent No. 16/154,630 was granted: ""Methods And Systems For Clustering Files” in the name of MinerEye Ltd.
Filing Date: October 8, 2018
Filing No: 15/154,630
Issue Date: October 7, 2020
3) MinerEye was recognized as the Winner of the 2020 Cyber Security Excellence Awards in the Data Classification Category.
4) MinerEye achieved an official ISO27001 certification.
5) We have acquired three new customers and three strategic partners in Europe and the US around Data Privacy projects that required DataTracker smart discovery in the cloud and on-premise data sources. These deals were closed thanks to the contribution to the efficiency of classifying data and business apps and services, such as CRM, marketing automation, and more. We've learned that corporate business processes such as HR, Legal, Finance, are at the highest risk. These business groups practice a high level of sharing files, signing off of internal documents, and using external cloud collaboration tools. With DataTracker we have been able to reduce the operational expenditures involved with cloudification, and the customers were able to ensure that only the data that is ‘migration-worthy,’ i.e. is valuable to the organization and all of its relevant stakeholders, is actually moved to the cloud. This required knowing which data should be moved and which shouldn’t, and which data must be protected versus that which can be archived or even (must be) deleted.
The immediate impact on our customers was around fast time-to-value, cost-saving in manual and tedious work, and coverage of vast amounts of data.
6) We have learned that mid-market and Small Medium Businesses do not have many alternative solutions to automate the discovery of risky data and these organizations are at the highest risk since they have the highest number of distinct cloud services. It is unclear at this point if these organizations will use this as a service (SaaS) or will prefer to run the application from their cloud instance and scan their synced end-point data without installing agents on their corporate laptops. This will require more market research and trial through partners going forward."
Filing Date: November 23, 2016
Filing No: 15/360,612
Issue Date: August 6, 2019
Patent No.: 10,372,731
Patent Term: 20 years from the filing date
2) United States Patent No. 16/154,630 was granted: ""Methods And Systems For Clustering Files” in the name of MinerEye Ltd.
Filing Date: October 8, 2018
Filing No: 15/154,630
Issue Date: October 7, 2020
3) MinerEye was recognized as the Winner of the 2020 Cyber Security Excellence Awards in the Data Classification Category.
4) MinerEye achieved an official ISO27001 certification.
5) We have acquired three new customers and three strategic partners in Europe and the US around Data Privacy projects that required DataTracker smart discovery in the cloud and on-premise data sources. These deals were closed thanks to the contribution to the efficiency of classifying data and business apps and services, such as CRM, marketing automation, and more. We've learned that corporate business processes such as HR, Legal, Finance, are at the highest risk. These business groups practice a high level of sharing files, signing off of internal documents, and using external cloud collaboration tools. With DataTracker we have been able to reduce the operational expenditures involved with cloudification, and the customers were able to ensure that only the data that is ‘migration-worthy,’ i.e. is valuable to the organization and all of its relevant stakeholders, is actually moved to the cloud. This required knowing which data should be moved and which shouldn’t, and which data must be protected versus that which can be archived or even (must be) deleted.
The immediate impact on our customers was around fast time-to-value, cost-saving in manual and tedious work, and coverage of vast amounts of data.
6) We have learned that mid-market and Small Medium Businesses do not have many alternative solutions to automate the discovery of risky data and these organizations are at the highest risk since they have the highest number of distinct cloud services. It is unclear at this point if these organizations will use this as a service (SaaS) or will prefer to run the application from their cloud instance and scan their synced end-point data without installing agents on their corporate laptops. This will require more market research and trial through partners going forward."