"...you've got to hang in there until the punch line. Some other things that Carrabis comes up with can seem absolutely dotty in the beginning. You may have the urge to throw up your hands, walk out and find somebody who makes sense. Some of the folks in the last class did that. They managed to miss some of the most mind blowing educational experiences they could have had. I suggest you give it time if it seems weird, pointless, confusing, or irrelevant in the beginning. I promise it will pay."
Exploratory Analysis has been expensive for many reasons. You need to have an idea what hole the noisy data you're interested in is in, what type of noisy data you're looking for, it's usually a hands-on job and not automated (scalability again), once performed the end result is "Okay, we performed due diligence so we know what we can't do and what we can't look at. Let's get back to something we can metricize", ...
These last two statements are key to our discussion moving forward; scalability and metricization (accountability). When we apply metrics to something we can make A=B and that means we have the ability to say "This is working, continue" or "That isn't working, stop." These "Do this, Don't do that" are action items. Keep these in mind for what follows in this arc.
Here I want to reintroduce pieces of the discussion I was having with Angie Brown, Strategic Services Consultant for Coremetrics. Angie is a big believer in accountability. She explained to me that "At the simplest reporting level all analytics packages use all the data. It's when you get into very complex reports that each analytics vendor gets to demonstrate their unique strengths because, at this level, you're winnowing out details to report on very specific items which don't require that all details necessarily be present."
It was Angie who -- thinking out loud and blue skying -- offered that where analytics needed to be is in a place where it could offer "Simple tools backed by incredibly complex analysis."
And this is where the NextStage staff begins to get nervous. Joseph (that's me) thinks he hears a question and goes into a fugue state until he solves it (Angie, Trish, Debrianna, Cindy, Dan, Susan and several others are chuckling reading this, I know).
Of course, more to follow...
Links for this arc:
- Articles on noisy data affecting analysis:
- The Critical Difference: Essays in the Contemporary Rhetoric of Reading
- Design and Purpose links:
- Semphonics Functionalism Paper
- IMediaConnectin Columns
- Chapter 7, "Experience versus Expectation", Reading Virtual Minds
- The Noisy Data Arc
- Posts on new web technologies:
- Posts mentioning WAA:
- Web Analytics Association Links:
- Web Analytics Vendors mentioned in this arc:
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