The Stacks: Part 2

Yesterday, you met SnowPlow, a new open source stack for web analytics.

Hopes for SnowPlow:

• That it will expose more web analysts to machine learning experiences with WEKA, MaHoot, R, or python

• That it will reduce the reporting efforts and increase data latency

• That it will drive better predictions and stronger optimization routines

Hopes for the Social Stack

Remember this?

(You can read the full post about Personal Knowledge Systems if you’re curious).

Stacks have powerful effects on the experiences that teams have. Tools alone aren’t guaranteed to generate amazing experiences, and incredible results. The real determinant is how those with great stances use those tools to realize those results. Tools are an intervening variable.

There’s a fairly heated debate happening among people who experience data through algorithms.

Greater exposure to the underlining relationships amongst variables should lead to better descriptions. Getting beyond the aggregated counts and down into comparing relationships amongst rows and columns ought to generate better explanations. Modeling keep causality ought to generate more accurate predictions and more provocative recommendations.

It depends on analysts themselves.

I believe that they all want greater impacts.

That’s my hope for the social stack.

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I’m Christopher Berry.
I tweet about analytics @cjpberry
I write at christopherberry.ca