{"id":7448,"date":"2017-07-18T08:46:37","date_gmt":"2017-07-18T08:46:37","guid":{"rendered":"https:\/\/rsoftsolution.com\/blog\/privitar-raises-16m-to-help-ensure-privacy-in-big-data-analytics.html"},"modified":"2017-07-18T08:46:37","modified_gmt":"2017-07-18T08:46:37","slug":"privitar-raises-16m-to-help-ensure-privacy-in-big-data-analytics","status":"publish","type":"post","link":"https:\/\/www.rbsitsoftwaresolution.in\/blog\/privitar-raises-16m-to-help-ensure-privacy-in-big-data-analytics.html","title":{"rendered":"Privitar raises $16M to help ensure privacy in big data analytics"},"content":{"rendered":"<p><!-- Begin: WordPress Article Content --><br \/>\n<img data-recalc-dims=\"1\" decoding=\"async\" src=\"https:\/\/i0.wp.com\/rsoftsolution.com\/blog\/wp-content\/plugins\/RSSPoster_PRO\/cache\/36f3a_gettyimages-159629750.jpg?w=640&#038;ssl=1\" class=\"\" \/><\/p>\n<p id=\"speakable-summary\">As <a href=\"javascript:void(0)\">data protection<\/a> \u2014 a set of laws and practices created across different markets to ensure that our sensitive information does not get leaked or shared without our permission \u2014 continues to gain priority in our rapidly expanding digital world, a UK startup called\u00a0<a href=\"javascript:void(0)\">Privitar<\/a> that is building tools to help organizations keep that data private has picked up $16 million in funding to expand its tech platform and take its business to the US market.<\/p>\n<p>The Series A round was led by France\u2019s Partech Ventures with strategic participation from CME Ventures (the investing arm of derivatives marketplace CME) and, interestingly, Salesforce Ventures. Previous investors IQ Capital, 24Haymarket and Illuminate Financial also participated, bringing the total raised by two year-old Privitar to <a href=\"javascript:void(0)\">around $21 million<\/a> (\u00a316.5 million in local currency).<\/p>\n<p>In an interview, CEO and co-founder Jason du Preez \u2014 who <a href=\"javascript:void(0)\">previously<\/a> founded and sold a data distribution company, m35, to Reuters \u2014 described Privitar as a \u201cprivacy engineering\u201d firm, which refers to a set of algorithms that are applied to data to help separate it from obvious and less obvious identifiers. This is not to be confused with more basic \u201canonymised\u201d data.<\/p>\n<p>\u201cOften what people mean by \u2018anonymised\u2019 is that they\u2019ve marked out basic identifiers, but as data becomes more complex there are other identifiers within the data that can be used to pinpoint a user, even without basics like name and date of birth, such as location,\u201d he said. \u201cThat is the problem we have solved, with methods that analyse the data and expose the holes.\u201d<\/p>\n<p>In Privatar\u2019s case, it offers\u00a0<a href=\"javascript:void(0)\">two products<\/a> today to help do this.<\/p>\n<p>Privitar Publisher, \u201ctakes sensitive data and applies a privacy policy to create an anonymised copy which can safely be used for investigative analytics, machine learning, and sharing with trusted parties\u201d by way of tokenization and encryption of identifying fields. And Privitar Lens is a \u201cprivacy-preserving query interface for reporting and statistical analysis. Privitar Lens allows analysts to perform sophisticated analytical queries of the data (e.g. counts, sums, histograms), but prevents direct access to the underlying sensitive data,\u201d which is also known as differential privacy. On top of the products itself, Privitar logs and audits all queries.<\/p>\n<p>Privitar is not the only company that has built products to address the next level of personal data protection that has arisen with the surge in big data analytics: <a href=\"javascript:void(0)\">Apple<\/a>, <a href=\"javascript:void(0)\">Microsoft<\/a>\u00a0(a trailblazer and early mover) and <a href=\"javascript:void(0)\">Google<\/a> have all started to make moves to implement differential privacy in their own data activities.<\/p>\n<p>Privitar is notable because it\u2019s building similar tools so that others can have and use the same kinds of policies that these big tech companies have built for themselves. Du Preez tells me that its first wave of users have been companies in financial services (unsurprisingly, as they have a lot of regulation around data protection that they need to comply with), as well as pharmaceutical and government organizations. \u201cWe\u2019re starting to expand across other industries,\u201d he said, \u201cbecause this is completely transferrable to other services.\u201d<\/p>\n<p>Now is a key moment for more products to help companies with data protection: cyber breaches, where data can equally be leaked in drips or rushed out in disastrous tsunamis, continue to take place, and with a growing amount of stolen data on the market, it\u2019s becoming all too easy for malicious hackers to apply their own big data magic to steal identities and do a lot of harm.<\/p>\n<p>To come up with solutions to make that data impossible to use in the first place is a very obvious and necessary line of defense, alongside all of the other cybersecurity services that have been developed to help with authentication, securing network perimeters and so on. By one estimate (provided by Privitar), there will be $50 billion spent by organizations on privacy engineering solutions annually.<\/p>\n<p>Unsurprisingly, the fact that Privitar is seizing that opportunity and doing it successfully is one reason why the company has raised what is a very decent round for a European startup.<\/p>\n<p>\u201cData-driven decision making and intelligence is becoming critical for all businesses. Firms cannot afford to compromise on privacy protection given the potential consequences to brand and reputation,\u201d said Jean-Marc Patouillaud, managing partner for Partech Ventures, in a statement. \u201cWe have decided to invest in Privitar because we see them as an excellent option for organisations that want to get the most of their data while ensuring full customer trust.\u201d<\/p>\n<p>One factor that will keep driving this is the big rush for big data: with so many of our activities and services now holding a digital component to them (if not being entirely digital now), it\u2019s given a rise to a vast amount of data that organizations are hoping to tap for business intelligence, and maybe more.<\/p>\n<p>\u201cBalancing the acceleration of advanced analytics and increasing data privacy concerns is an ongoing challenge for financial institutions and other highly regulated industries globally,\u201d said Rumi Morales, head of CME Ventures. \u201cCME Ventures is excited to back Privitar\u2019s pioneering technology and world-class team, as they tackle this important issue.\u201d<\/p>\n<p><!-- End: WordPress Article Content --><\/p>\n<p><small>Featured Image: <a href=\"javascript:void(0)\">Maciej Frolow<\/a>\/Getty Images<\/small><\/p>\n<p>Article source: http:\/\/feedproxy.google.com\/~r\/techcrunchIt\/~3\/aZzKB-GL2LI\/<\/p>","protected":false},"excerpt":{"rendered":"<p>As data protection \u2014 a set of laws and practices created across different markets to ensure that our sensitive information does not get leaked or shared without our permission \u2014 <\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[19],"tags":[25],"class_list":["post-7448","post","type-post","status-publish","format-standard","hentry","category-enterprise-software","tag-enterprise"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.3 - 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