lak11 opening keynote

Pragmatic analytics: insight, representation and structure

Tony HirstDepartment of Communication and Systems,

The Open University, UK

Let us start….

…with a little context

“Enterprise Driven” analytics

http://www.jiscinfonet.ac.uk/bi

Contribute to development and delivery of robust models, tools, skills and resources to enable

segmentation, competitor and market analysis and data mining within the Campaign Planning Team

and more widely within Marketing and Sales.

Corporate Data and MI Analyst, Marketing

For example... Experian's Mosaic UK combines over 440 separate data sources and divides the UK adult

population into 69 different types and fifteen groups … at household address

or postcode level.

Contribute to optimising the University’s customer targeting capability via regular reappraisal of segmentation policy with a

view to increasing market share in high yield segments

Corporate Data and MI Analyst, Marketing

Corporate Data and MI Analyst, Marketing

Segment the prospect data mart by developing key prospect indicators to provide Response, Reservation,

Registration, Retention and other key metric predictions for each.

advertising

prospectus

registration

retention

graduation

fundraising

“Course Choice Analytics”

The Goog Course Page

QualificationDescription

Course Search

Related Courses

“Course Choice Analytics”

The Goog Course Page

QualificationDescription

Course Search

Related Courses

Oer disc

overy

Looking for structure

“Visual analytics”

Graph based representations

Nodes: id, label

Edges: id(1), id(2)

advertising

prospectus

registration

retention

graduation

fundraising

advertising

prospectus

registration

retention

graduation

fundraising

AcadEmic analytics

“Student Centred” learning analytics

Descriptive reports

Prescriptive models

Predictive voodoo

Descriptive reports

via Dave Pattern @daveyp

“Negative feedback, closed loop control system”

Prescriptive models

Time series demonstrating:

- trend- seasonality/periodicity- noise

Linear detrend (green) and first difference (blue)

Autocorrelation

Linear detrend (green) and first difference (blue)

Autocorrelation

Voodoo Magic

(a.k.a. blackbox recommenders)

supervised learning(desired output for given input)

Input patterns

Output Patterns

“recommendation engine”

Desired outputActual output

Course Analytics(Google Analytics)

SitewideTracking(Site Analytics)

Library Analytics(Google Analytics)

VLEStats

Beware headline figures…

Do you really mean that?

http://eagereyes.org/criticism/anscombes-quartet

http://eagereyes.org/criticism/anscombes-quartet

Simpson’s Paradox

Segmentation is critical…

http://code.google.com/apis/analytics/docs/gdata/gdataExplorer.html

“Public signals”

Facebook: Course Profiles

Friendfeed

Commenters

“Discovered networks”

Bipartite Graph

Reach:Double hit audience for “To lie or not to lie”

< questions? >