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

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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

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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

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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

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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