get in the zone -- how to visualize success quickly

Grab some coffee and enjoy the pre-show banter before the top of the hour!

The Briefing Room

Get in the Zone – How to Visualize Success Quickly

Twitter Tag: #briefr The Briefing Room

Welcome

Host: Eric Kavanagh

[email protected] @eric_kavanagh


!   Reveal the essential characteristics of enterprise software, good and bad

!   Provide a forum for detailed analysis of today’s innovative technologies

!   Give vendors a chance to explain their product to savvy analysts

!   Allow audience members to pose serious questions... and get answers!

Mission


Topics

2014 Editorial Calendar at www.insideanalysis.com/webcasts/the-briefing-room

This Month: INNOVATIVE TECHNOLOGY

August: BIG DATA ECOSYSTEM

September: INTEGRATION


Analyst: Robin Bloor

Robin Bloor is Chief Analyst at The Bloor Group

[email protected] @robinbloor


IBM

!   IBM offers a full suite of business analytics products, from BI and dashboards to predictive and advanced analytics

!   IBM Cognos includes the Rapidly Adaptive Visualization Engine (RAVE), a flexible and extensible solution designed to enhance insight through advanced visuals and graphics

!   RAVE is the engine behind Many Eyes, a free web-based tool that allows users to upload public data sets, create complex visualizations and publish back out to the Web


Guest: Brent Winsor

Brent Winsor is Product Marketing Manager at IBM Business Analytics. He has over 14 years of software product marketing experience in both large and small software companies. He has positioned and launched software products in the supply chain, office productivity, managed services and business analytics markets. He has an MBA with a marketing focus from Dalhousie University in Halifax, Canada.

© 2014 IBM Corporation

Visualization – Gaining Value From Your Data

June 17, 2014

© 2014 IBM Corporation 11

GAINING VALUE FROM YOUR DATA

Visualization

Importance of visualization

Understanding data

RAVE extensible visualization

Creating effective visualizations


DATA VISUALIZATION SIMPLIFYING THE COMPLEX

Daily Amount of Data Created =2.5 exabytes

Created by companies:

25%

Created by individuals: 75%

Oil Refinery: 750GB

Wind Turbine: 144GB

Twitter: 4TB

YouTube: 8.6TB

Facebook: 15TB

Email: 21PB

Terabyte (TB)=1000 Gigabytes Petabyte (PB)= 1 Million Gigabytes Exabyte= 1 Billion Gigabytes

Source: http://marscommons.marsdd.com/the-data-visualizers/market


VISUALIZING 600,000 TRANSACTIONS


SPREADSHEETS CAN’T FULLY UNLOCK THE VALUE FROM DATA


“A great visualization is worth a million data points”

http://en.wikipedia.org/wiki/Anscombe%27s_quartet

PATTERNS DETECTED MORE EASILY THROUGH VISUALS

•  Inability to see patterns

•  All data points can’t fit on a single screen

•  Deep and broad data sets not shown effectively

Driving Factors for Visualization

IBM Solution Rapidly Adaptive Visualization Engine (RAVE)

•  A simple descriptive language to describe a chart •  Flexible enough to describe all known charts and extensible to

describe new and innovative visualizations


SPSS Analytic Catalyst

Cognos Insight

Analytical Decision Management

Cognos Business Intelligence

RAVE– The Engine Driving IBM Visualizations


IBM Watson Analytics The Next Generation Of Data Discovery


The new way… The old way…

Analytics & Visualization Engine

Visualization Description

Analytics & RAVE Visualization Engine

RAVE Creating New Visualizations For The Marketplace


Visualizations Integrate With Cognos BI Supported On Mobile


IBM Cognos Visualization Customizer


DEMO - Leveraging RAVE Visualizations in Cognos Business Intelligence


The Upside of Flexibility


The Downside of Flexibility


A Successful Visualization has 4 key elements

Purpose Why this visualization

Content What needs to be visualized

Structure How should we visualize it

Formatting How useful is it

Noah Iliinsky – Visualiza(on Expert

Four Pillars of Visualization



Purpose and Content

1. Who is my customer? 2. What are their actions/decisions that I need to inform? 3. What specific questions do I need to answer? 4. What data do I need to display? 5. What relationships are represented in the data?



•  The right structure allows you to represent many dimensions clearly

•  The purpose and content of your visualization leads to the appropriate structure

Structure The Most Important Design Decision


•  Formatting is the frosting on your visualization; it should enhance, not distract.

The Frosting is the Formatting



Create rapid, more innovative visualizations

Watson Analytics

IBM Center for Advanced Visualization

The IBM Difference


Visit AnalyticsZone.com for:

Extensible visualization gallery

Expert articles

Best practices

What’s Next?


Perceptions & Questions

Analyst: Robin Bloor


Minard’s Visualization

Dimensions: Advance/retreat (color), geographical location, number of men, temperature, distance & time


Beyond The Madd(en)ing Spreadsheet

Most of the time you do not just view data, you interact with it:

!   Anatomically – via drill down and summary

!   Mathematically – via algorithms

!   Exploratively – via a variety of perspectives

!   Topologically – through its visual appearance


The Bald Options

For data, there are two possible approaches:

!   Reports: Lists, groupings, summaries and verbal comment

!   Visualization: Illustrations, graphs, charts, diagrams, photographs, animations

Of course, they are not mutually exclusive. They are best combined


Consumers & Explorers

SPECIFIC USER

TYPES: Needs to be informed/enabled in an easily digested manner

THE CONSUMER

Needs to be provided with: • an exploratory

capability • a versatile set of tools • a versatile set of

visualizations •  training/education

THE EXPLORER


The Nature of Learning

Learning: !  The visual cortex is the

largest neural system in the brain and hence often dominates learning

!  Differences noticed by the senses draw attention and have greater impact.

!  Words and pictures are inevitably cross-bred. There is logic, but also intuition.

!  Exploration => learning; articulation => learning; teaching => learning


!  What does IBM know about the effectiveness of any specific visualization and how do we know it? How is it measured?

!  Is there a relationship between visualization and data volumes? If so, what is it?

!  What does IBM know about animation and cognition, if anything? Does RAVE enable animation? What new visualizations have been created?


!  Are some people poor at deriving meaning from visualization – and yet skilled in other ways?

!  What is the learning dimension and how is it characterized?

!  You suggest that there are best practices. How do we know – what research has been done? Are there cultural variances?


Upcoming Topics

www.insideanalysis.com

2014 Editorial Calendar at www.insideanalysis.com/webcasts/the-briefing-room

This Month: INNOVATIVE TECHNOLOGY

August: BIG DATA ECOSYSTEM

September: INTEGRATION


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