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An overview of data mining and data visualisation from Mezzo Labs' "Getting Ahead in Web Analytics" event in February 2014.
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Data Mining & Data Visualisation
Lance NelsonMezzo LabsFebruary 2014
Data visualisation
Definition
“The creation and study of the visual representation of data” (Wikipedia)
“The main goal of data visualisation is to communicate information clearly and effectively through graphical means.” (Vitaly Friedman, ‘Data Visualisation and Infographics’ article, Smashingmagazine.com)
Column chart Streamgraph
Treemap Scatter plot
““
What do you need it for?
- Communicate business intelligence
- Interpretation of the data in order to gain insight
- Keep a closer eye on your business’ vital signs
Main vendors
There are two types of data visualisation products:
a) Presentation-only• View your data via a series
of widgets
b) Simple drill-down• Interact with the data• Measure campaign
effectiveness• Add comments/insight• Manage users
a) Presentation-only
Monitor your business’ vital signs
b) Simple drill-down
‘Democratises’ the software by encouraging collaboration
Functionality
Graphic courtesy of Klipfolio
A word of caution…
They say “a picture paints a thousand words”…(or in our case, numbers)
BUT DOES IT?
“An ideal visualization should not only communicate clearly, but stimulate viewer engagement and attention”
How To Make Data Look Sexy, Fernanda Viegas and Martin Wattenberg, CNN.com, 2011
Data mining
““
Definitions
• The analysis of historical business activities to reveal hidden patterns and trends.
– Wikipedia
• Data mining’s main function is to increase ROI…primarily used today by companies with a strong consumer focus - retail, financial, communication, and marketing.
– Jason Frand, UCLA
““
What do you use it for?
• Sell more products, increase ROI• Increase the effectiveness of campaigns• Attract new customers and increase customer loyalty
Data mining helps to:• Determine sales trends• Segment customers based on activity and demographics• Develop marketing campaigns• Predict customer loyalty and future trends
Data sources: databases, flat
files, feeds
Data ware-house or mapping scheme
Search for patterns: queries,
rules, neural net, mathemati
cal learning, statistics
Revise and refine queries
Analyst reviews output
Report findings
Interpret results
Take action
Pre-process data: collect,
clean and store
Main Vendors
There are two types of data mining products:
a) Data-centric• Analyse offline and online data
b) Web-centric• Analyse purely online data
Main Vendors
SAS• Predictive analytics• Visual analytics• Forecasting and econometrics• Text analytics
ijento• Started as a web analytics
company• Marketing optimisation• Customer experience management• Visualisation
Output
Output
+
Summary
Use data visualisation to:
Monitor your business’ KPIs and/or enable data-driven decisions through collaboration and sharing
Use data mining to:
Learn from your customers’ past behaviour and use this to predict their future behaviour