Stephane Hamel posted an excellent article today on “The Three Heads of Online Analytics“. To summarize: To succeed in online analytics, we need an analytics competency center. Start with the business in mind, get the technology in place, and then analyze to generate insights. Analyze your weaknesses and zap them, try adapting ‘paired programming’ that’s common in agile methods. I commented: There are T’s, S’s, and A’s. T’s are technical analysts. S’s are strategic analysts. A’s are Analytics (actual analytics, not fake BI reporting) analytics. Hiring a competent T-A is exceptional. Finding a S-A is getting easier. Finding a good T-S-A is damn near impossible. Most of them are consultants. Web analysts need to identify their weaknesses, be it T,[…]
Month: January 2012
Audrey Watters wrote a good article about Data Science in 2011 for O’Reilly Radar. Audrey cites three big events / trends: Hadoop, an open source distributed computing framework, became ubiquitous. More Data, More Privacy Problems – citing the Apple scandal as an example. Open Data at an Inflection Point. (With a great shoutout to my friends at BuzzData!) Editorial: Even Hadoop has warts (gasp!?!111shiftoneone), but so far there are good anecdotes about it working out well for many companies, and, you can expect a few horror stories in 2012. The devices we’re carrying and our own behaviors are generating more data than ever – and people – that means you – need to be aware of when they’re consenting to[…]
Steve Miller authored a very good article about Data Science Skepticism over at Information Management. I’ve previously written about Data Science and shared an excellent video about what makes a great data scientist. Both posts are expanded primers on the emerging field. The TL;DR version is: A Data Scientist (DS) sits at the intersection of computer science, statistical methods, and business. I won’t define what Business Intelligence (BI) is. There’s an EMC study making the rounds. Steve Miller takes exception to some portions of that study. To summarize Steve Miller: Findings from the EMC survey made certain statements about BI’s that are unnecessarily polarizing, and should be viewed with suspicion by data scientists (which should be their natural inclination anyway).[…]
Tyler Nichols writes: “I am done with the freemium model“. Tyler divided all the users of his service into two groups: free and paid. He measured the behaviors of each group. He found that the free group was detrimental to his business because: They emailed more questions on average than paid people. They hit the spam button when he emailed them with a follow-up, paid people didn’t. Free customers were not worth the maintenance costs they caused. Hacker News and other communities replied (paraphrased): Free people were not as engaged, and therefore more wreckless. It was a santa letter generator, which has low repeat value after the season. The plural of anecdote isn’t evidence, you’ve added little value to freemium[…]