An amazing Partnership between Dathena, PwC and Nvidia
This alliance combines PwC’s cyber security and data protection services expertise with Dathena’s unique data governance software to improve data classification, security anomaly detection, and the protection of sensitive and personal information.READ FULL PRESS RELEASE
As organisations wake up to the huge potential of digital transformation, they are also becoming alert to the need for cybersecurity. Put simply, this means safeguarding your most critical information by detecting, responding to and resolving threats resulting from mismanaged or unsecured sensitive data.
An unavoidable part of this process is the ability to keep track of this data. The trouble is that large and medium size organisations are struggling to identify and classify the tremendous amount of unstructured electronic data they generate and store.
Until recently, and according to PwC, the information security systems available in the marketplace weren’t keeping up with the rapidly changing business needs and regulatory requirements in this area. But for PwC this was a critical piece of the cyber security jigsaw, so they kept searching. They had a fairly tough set of requirements, including:
Christopher Muffat, CEO at Dathena and Yan Borboën, Partner Cybersecurity at PwC
Yan Borboën, Partner Cybersecurity at PwC and Philippe Eyriès, Chairman of the board at Dathena
Dathena has been able to combine machine learning technology with industry information security experience and best practices to develop what we believe to be the most innovative and accurate data governance and security platform − which is focused entirely on the needs of the customers and fits perfectly with risk managers, compliance officers, and the concerns of data protection officers. Importantly for PwC, it can also be interfaced with existing governance, risk management, and compliance (GRC) tools, data labelling plug-ins, and Data Loss Prevention (DLP) solutions.
The result is a brand-new strategic alliance combining PwC Digital Services’ multidisciplinary capabilities in digital strategy, transformation, experience and design, data analytics and cybersecurity, and Dathena’s innovative and accurate data governance solution − using cutting edge machine learning and artificial intelligence technologies. In concrete terms, this means PwC has decided to create a Center of Excellence (CoE) for Dathena in Switzerland. The CoE will allow PwC to acquire the expertise to deliver best-in-class services anywhere in the world.
"After intensive discussions with Dathena, we knew we had found a partner that would enable us to achieve our goals to deliver the best data governance and security solutions. Their data governance platform will revolutionise our data governance's offering.”
Yan Borboën, Partner at PwC Switzerland
Accelerating AI startups with powerful GPU tools, tech, and deep learning expertise
Thanks to Dathena's artificial intelligence and machine learning capabilities, we have been invited to join NVIDIA inception program. This allows us to develop our technology even further and continue to be at the forefront of innovation.
The NVIDIA Inception Program is designed to nurture startups who are revolutionising industries with advances in artificial Intelligence (AI) and data science. Designed as a virtual incubator program, Inception helps members during critical stages of product development, prototyping, and deployment.
Data scientists in both industry and academia have been using GPUs for machine learning to make groundbreaking improvements across a variety of applications including image classification, video analytics, speech recognition and natural language processing. In particular, Deep Learning – the use of sophisticated, multi-level “deep” neural networks to create systems that can perform feature detection from massive amounts of unlabeled training data – is an area that has been seeing significant investment and research.
Although machine learning has been around for decades, two relatively recent trends have sparked widespread use of machine learning: the availability of massive amounts of training data, and powerful and efficient parallel computing provided by GPU computing. GPUs are used to train these deep neural networks using far larger training sets, in an order of magnitude less time, using far less datacenter infrastructure. GPUs are also being used to run these trained machine learning models to do classification and prediction in the cloud, supporting far more data volume and throughput with less power and infrastructure.
Early adopters of GPU accelerators for machine learning include many of the largest web and social media companies, along with top tier research institutions in data science and machine learning. With thousands of computational cores and 10-100x application throughput compared to CPUs alone, GPUs have become the processor of choice for processing big data for data scientists.
Learn more here.