We’re back with the fourth post in our series on how to get value from your data, including how to ensure that new “data” and “analytics” products are designed for successful delivery to new and existing customers.
In the previous posts in this series, we discussed our methodology and what is required in terms of understanding your target customer—who they are and what they need—as well as making sure you have the right Team in place to work on the project. In this post, we are going to discuss how you build your Data Ecosystem:
- What is needed to ensure that data processes will support the new product(s)?
- How do you identify appropriate data partners and enhancements?
- What privacy- and security-related issues must you be aware of and address?
Trend #1: Digital Advertising Comes of Age and Continues to Propel the Growth of Data Brokers and Markets
Authors’ Note: As promised, this is trend number one in our take on the top ten privacy trends or the more things change, the more they stay the same. Although similar to David Lettermen’s Top Ten lists, our list is not as funny (unless we get points for sarcasm). We would like to remind you that sifting through the media coverage, books, blog posts, and research studies has been no easy task and trying to understand how all of it fits into the larger privacy landscape has been even harder. Added to that, our list is sure to elicit a litany of trends that we missed. We certainly hope that it does and welcome your input in our comments section! Now, on with the trend number one!
It is safe to say that continued media attention (mostly negative) has not had an impact on the rising use of third party tracking mechanisms to collect personal information. According to the Web Privacy Census, an undertaking sponsored by the Berkeley Center for Law and Technology, which measures and benchmarks Internet tracking over time:
- The number of cookies discovered on the top 100, 1,000, and 25,000 websites are all significantly increasing. For example, in May of 2012 5,795 cookies were found on the top 100 sites and in October of 2012 the number reached 6,485.
- The percentage of cookies set by a third party host was 84.7%. In other words, most of us are being tracked by a host of parties that we have no data collection agreement with.
- The top trackers were BlueKai (the largest online auction marketplace), Rubicon Project (one of the larger real-time bidding systems that sells ad space on web pages), and Adnxs (the advertising exchange for advertising exchanges).
We’ve been promising an update to our book, Privacy and Big Data, since the just pre- and mostly post-Snowden era. When we proposed and wrote the book it was to fill a void. At the time, there was a lack of mainstream attention to the issues of privacy by the media and a lack of understanding of the issues and implications we all face in the digital world. As tech veterans of long standing, we have seen our world transformed for better and for worse by our industry. Much of the “worst” we chronicled in our book and at the time its release, many relegated our book and ourselves to the “foil hat” and “black helicopter” brigade. Yes, that was a “we told you so” but we promise it’s the last one.
Then came the Snowden revelations which raised its own hailstorm of media attention, information, misinformation, and disinformation (primarily by our government officials, legislative leaders, and the President as well as the Prime Minister of the UK) on exactly how our data was being collected and what it was being used for. Cynics though we are, we wondered if digital privacy issues had finally reached a tipping point, that we would have a national conversation about civil liberties, how to fix FISA, what is the acceptable collection and use of our data by commercial and government entities, and moving forward, how our liberties and data could be protected from corporate and government spying. (more…)
By Mary Ludloff
Although this year has been extremely busy for us, Terence and I always find time for this event: The Privacy Identity Innovation Conference. Natalie Fonseca, the Co-Founder and Executive Producer of it, is the driving force behind its ongoing success. This year’s program focuses on:
“… the latest developments in areas like mobile, biometrics, the Internet of Things and big data. Learn about emerging trends and business models driving the personal information economy, and get guidance on developing strategies and best practices to build trust with your users.” (more…)
Welcome back to the second post in our series on how to get value from your data. As we stated in a previous post:
“Data, without the proper use of analytics, is meaningless. If data is the new oil, think of analytics as the oil drills—you need both to be successful.”
Of course, getting to “success” is not easy as anyone involved in an analytics project will tell you. This series walks you through our methodology on what it takes—from inception to proof of concept to implementation and deployment—to navigate project pitfalls. Now most of us have been involved with great analytics projects that answered no real need. In this post, we take a look at the customer, their pain points, and what benefits they may derive from your analytics project. In other words: Who is your target customer? (more…)
We read an interesting paper and post about Google Flu Trends (GFT) and its foibles last week. The paper points out a couple of lessons that those of us living in the big data analytics world have learned the hard way but the dangers are worth revisiting as tools like ours (AnalyticsPBI for Azure) begin to move big data analytics into the mainstream of organizational practices. After all, our tool (and others like it) makes it easy and even fun for analytics junkies to use all those available zettabytes of data and answer questions that they’ve long wondered about. But the paper also reminded us of the dangers of ignoring the natural cycles of an analytics process that we talked about in this recent post. If Google followed the PatternBuilders Analytics Methodology, they might have avoided many of the errors that GFT is now spitting out. In fact, the authors of the paper point out that:
“Although not widely reported until 2013, the new GFT has been persistently overestimating flu prevalence for a much longer time. GFT also missed by a very large margin in the 2011-2012 flu season and has missed high for 100 out of 108 weeks starting with August 2011… This pattern means that GFT overlooks considerable information that could be extracted by traditional statistical methods.”
This overestimation is attributed to two primary factors: data hubris and algorithm dynamics. (more…)
A recent conversation with a client reminded me that no matter how crazy and exciting the Big Data world gets, it is still critical to understand what your goals are and where you are in the process of reaching those goals. Having a good foundation in “what’s important” is critical before you jump into the wild world of Big Analytics.
For example, in big data (well, actually all data but I digress) “Reporting” and “Analytics” are very different functions. But I often find our customers and prospects grappling with how to distinguish one from the other and as a result, confusing reporting with analysis and losing track of their real goals.