This post was written by Mark Melodia, Cynthia O'Donoghue, Paul Bond and Frederick Lah.
Next week, Reed Smith will host a conference on “Big Data Monetization” at the Quadrus Conference Center in Silicon Valley (8:30-11:30 a.m. PDT). As we gear up, we wanted to share some of our thoughts on this notion of Big Data and give you a preview of the types of issues we’ll be tackling at the conference.
Big Data is an amorphous term, one that has taken on different meanings in different contexts. In general, Big Data is a term used to characterize the accumulation of data, especially for data sets that may not be usable for analysis by themselves. The term does not just encompass the small subset of companies that actually provides data analytics, or that exists for the sole purpose of monetizing personal information and habit data, but rather extends to any significant company participating in the digital data-driven economy.
Virtually every company, in every industry, is now an information and technology company. Companies run on Big Data, whether it be customer information, employee information, or competitive intelligence. Companies store, share, and use that information in increasingly complex ways, taking advantage of cloud-based solutions and revolutions in analytics, and finding ways to turn these massive databases into revenue – for example, by creating tailored advertisements based on customer shopping preferences or online browsing history. There is no doubt a plethora of opportunities for retailers, health care providers, banks, energy companies, website operators, and data brokers alike in Big Data.
Of course, using Big Data comes with its own set of risks. Companies need to ensure their disclosures are up-to-date and accurate about their information practices, and there may be laws or regulations on the collection and use of information depending on the types of data and data subjects involved. Both Congress and the Federal Trade Commission have also recently raised concerns about data brokers. In addition, some customers may feel uneasy with the notion that a company has too much information about them, thus drawing the attention of class action plaintiffs’ counsel. And, of course, having such deep databases of personal information highlights the importance of keeping information safe and secure. The more valuable information a company holds, the more magnified the threats of data theft and data loss become. The key with monetizing Big Data is striking the balance between risk and reward.
Our Data Privacy, Security & Management team has extensive experience providing privacy compliance advice to clients, drawing upon our knowledge gained in defending more than five dozen privacy class actions and three Multidistrict Litigations; our day-to-day operational experience answering questions from our technology, financial, health, and energy clients; and our diverse skill-set that includes engineers, software developers, cybersecurity and other technology professionals; former regulators and former in-house counsel at global banks; asset managers; and insurers. Earlier this month, Mark Melodia and Paul Bond were featured in the cover story of Law Technology News, “Defending Big Data”. Mark also recently did a podcast on “Defending Big Data”. We continue to stay on top of this area.
At the “Big Data Monetization” conference next week, our panel of experts will be tackling the following types of questions:
- Why should a corporate officer or director or investor care about issues with Big Data?
- What is the current regulatory landscape for Big Data?
- What are the biggest challenges for Big Data as it operates in the United States and globally?
- How does the issue of data ownership arise for Big Data?
- What types of litigation risks exist for Big Data
- How does the so-called concept of the "right to be forgotten” impact Big Data?
- How does insurance play a role in mitigating the risks that come with Big Data?
We look forward to seeing many of you next week.