"Strata SC 2013" entries
Privacy in the Online Ecosystem: Obligations and Best Practices Are Evolving
Preview of upcoming session at Strata Santa Clara
At the end of 2012, the Federal Trade Commission (“FTC”) hosted the public workshop, “The Big Picture – Comprehensive Online Data Collection,” which focused on privacy concerns relating to the comprehensive collection of consumer online data by Internet service providers (“ISPs”), operating systems, browsers, search engines, and social media. During the workshop, panelists debated the impact of service providers’ ability to collect data about computer and device users across unaffiliated websites, including when some entities have no direct relationship with such users.
As one example of the issues raised by the panelists, Professor Neil Richards, from the Washington University in St. Louis School of Law, stated that, despite its benefits, comprehensive data collection infringes on the concept of “intellectual privacy,” which is predicated on consumers’ ability to freely search, interact, and express themselves online. Professor Richards also stated that comprehensive data collection is creating a transformational power shift in which businesses can effectively persuade consumers based on their knowledge of consumer preferences. Yet, according to Professor Richards, few consumers actually understand “the basis of the bargain,” or the extent to which their information is being collected.
Building recommendation platforms with Hadoop
Preview of upcoming session at the Strata Conference
Recommendations are making their way into more and more products. Using larger datasets are significantly improving the recommendations. Hadoop is being increasingly used for building out the recommendation platforms. Some of the examples of Recommendations include product recommendations, merchant recommendations, content recommendations, social recommendations, query recommendation, display and search ads.
With the number of options available to the users ever increasing, the attention span of customers is getting lower and lower at the very fast pace. At any given moment, the customers are getting used to seeing their best choices right in front of them. In such a scenario, we see recommendations powering more and more features of the products and driving user interaction. Hence companies are looking for more ways to minutely target customers at the right time. This brings in big data into the picture. Succeeding with data and building new markets, or changing the existing markets is the game being played in many high stake scenarios. Some companies have found the way to build their big data recommendation/machine learning platform giving them the edge in bringing better and better products ever faster to the market. Hence, there is a strong case for looking at recommendations/machine learning on big data as a platform in a company, rather than something of a black box that magically produces the right results. The platform allows us to build various other features like fraud detection, spam detection, content enrichment and serving etc. making it viable in the long run. It is not just about recommendations.
Tax season + your identity = bucket loads of easy money for fraudsters
Take control of your identity and make sure your electronic footprint works for you.
Recently, the Wall Street Journal published an article discussing the explosion of tax-identity theft, which has ballooned to 1.1 million cases in 2011 from 51,700 in 2008. The Wall Street Journal mentioned that the Treasury Inspector General for Tax Administration reported an additional 1.5 million potentially fraudulent 2011 tax refunds totaling in excess of $5.2 billion.
What is the cause of this? Taxpayers now have the option to file their taxes online and receive their refunds directly deposited into bank accounts, and this tax filing method creates all kinds of opportunities for electronic fraud.
How does this affect you? Fraudsters who have certain pieces of your data can file a tax return under your identity and receive your refund. Fraudsters look for “at-risk” identities that they can use in scale to scam refunds out of the IRS. “At risk” identities include deceased identities, identities of minors, and legitimate citizens. Fraudsters only need a valid name and social security number combination. How much time, effort and money do you think it would take you to convince the IRS that a fraudster stole your identity, filed your taxes and received your refund? Even though this trend is on the rise and the government has seen it, the onus would still be on you, to prove that you were defrauded.
Exploring web standards for high data density visualizations
A sneak peek at an upcoming visualization session from the 2013 Strata Conference in Santa Clara, Calif.
Strata Editor’s Note: Over the next few weeks, the Strata Community Site will be providing sneak peeks of upcoming sessions at the Strata Conference in Santa Clara. Nicolas’ sneak peek is the first in this series.
Last year was a great year for data visualization at Twitter. Our Analytics team expanded and created a dedicated data visualization team, and some of our projects were released publicly with great feedback.
Our first public interactive of 2012 was a fun way to expose how the Eurocup was experienced at Twitter. You can see in this organic visualization how people cheered for their teams during each match, and how the tension and volume of tweets increased towards the finals.
