#BigDataMgmt chat: Big data, little privacy?
If you’re an organization that’s collecting that data, what are you doing to protect it and, thus, keep the trust of your customers? What technology and legal compliance challenges are you facing?
These are some of the issues we will examine in this #BigDataMgmt chat titled, “Big data, little privacy?” Our special guests for the chat are Jules Polonetsky, director, Future of Privacy Forum; Richard R. Lee: IBM Champion for Information Management; and Vishal Kumar, entrepreneur, innovator and author. Also joining will be IBM subject matter experts James Kobielus, big data evangelist, and Tom Deutsch, program director for big data and advanced analytics.
Follow along and join the discussion using the hashtag #BigDataMgmt. Here are the questions we’ll be discussing as well as reference articles to help inspire the January 8 conversation on Wednesday, January 22, 12:00 p.m. EST.
- When can an organization collect and use data without consent?
- Who owns data: the individual or the organization collecting it? Why?
- Should your organization rely on policy and law to determine efforts for privacy?
- How does the market punish those that do not protect data? Any examples?
- What’s the biggest threat to big data privacy? External attackers, data misuse, accidental disclosure?
- What are technology barriers preventing organizations from achieving privacy compliance?
- Are you concerned about security of centralized data in #Hadoop? Why/why not?
- How can you have best of both worlds: flexibility of #Hadoop AND secure data in new #bigdata tech?
#BigDataMgmt reference articles
- The State of the World on Data Privacy – Videochat panel discussion
- Privacy by Design in the Age of Big Data – white paper
- A New Privacy Paradigm for the Internet of Things – white paper
- Privacy and Big Data: Making Ends Meet – blog post
- Privacy in the Age of Big Data: A Time for Big Decisions – blog post
- Judged by the Tin Man: Individual Rights in the Age of Big Data – journal abstract
- Big Data for All: Privacy and User Control in the Age of Analytics – journal abstract
Jules Polonetsky (@JulesPolonetsky) is executive director of the Future of Privacy Forum, a Washington, D.C.-based think tank that seeks to advance responsible data practices. Prior to that, he held the role of chief privacy officer at AOL and DoubleClick. He was also previously Commissioner of Consumer Affairs for New York City and an elected New York State Assemblyman.
Vishal Kumar (@VishalTX) is passionate about product management, innovations, assisting startups with their strategic and tactical issues. He has led initiatives in social media, customer experience, systems, performance and automation. For the last 12 years, he has been, in his own words, a “web analytics, software developer, and systems junkie.” He holds two U.S. and four Indian technology patents.
Richard Lee (@InfoMgmtExec), management consultant with IMECS, LLC. For more than 30 years, Richard has helped guide companies in their business strategy and transformation. His areas of expertise include organizational change management, governance, risk and compliance. He speaks at conferences around the world on key business issues related to enterprise information management and data governance. He is an IBM Champion.
As IBM's big data evangelist, James Kobielus (@jameskobielus) is IBM senior program director, Product Marketing, Big Data & Analytics solutions. He is an industry veteran, a popular speaker and social media participant as well as a thought leader in big data, Hadoop, enterprise data warehousing, advanced analytics, business intelligence, data management and next best action technologies.
Tom Deutsch (@thomasdeutsch) played a formative role in the transition of Hadoop-based technology from IBM Research to IBM Software Group, and he continues to be involved with IBM Research big data activities and their transition from Research to commercial products. His team created the IBM BigInsights Hadoop-based product and he also co-authored the popular books Understanding Big Data.