With the explosion of big data analytics the last years, more customers or citizens are concerned about the usage of the personal data. Most companies and organizations are not transparent on how they use data on their customers.
This creates mistrust with the customers which is even enlarged when the data stored on the servers of the companies are hacked and made public. These trends, e.g. usage of (big) data to analyze customer behavior and the increasing hacking attempts that violates the privacy of their customers has made the issue of personal data more compelling.
Personal data implies that companies and organization become more transparent about the existence and usage of customer data. Because predictive analytics will be a growing source of competitive advantage in future, having customers that trust companies to protect their privacy will become more important. Companies that are transparent about the information they gather, give customers control of their personal data (usage of the data), and offer fair value in return for it will be trusted and will earn ongoing and even expanded access. Those that conceal how they use personal data and fail to provide value for it stand to lose customers’ goodwill—and their business.
Personal data alone will not solve possible security breaches and the attempts of hackers to make customer data public, but we believe transparency and an improved trust relationship with the customers will decrease the negative impact of those security breaches.
Increased awareness of personal data by companies, and more regulations by governments on privacy and personal data will requires that applications that have a new architecture that takes personal data features into account. The other trend that companies use more big data architectures for their daily business operations has lead us to create a new IT application architecture framework that takes all these trends into consideration. Our framework is based on the 7 privacy by design principles, developed by Privacy by Design and the technological requirements listed by the President’s Council of Advisors for Science & Technology (PCAST).
The proposed big data architecture of our personal data framework is based on the usage of a NoSQL database (Accumulo) that has security included in his design with cell-level visibility rules and that allows storage of petabytes of data. Another important component of the framework is Spark for all data transformation, enrichment processes and advanced analytics.
What we offer:
Social-3 offers a solution to create a personal data strategy and infrastructure that allows gaining customer trust, including ways to monetize data usage. We offer in-depth information on personal data architecture and system design. Our personal data proof-of-concept application provides more technical information on how to implement this architecture in a big data environment.