Tips for Creating Rich, Visual, and Actionable

User Experiences

Making Data Beautiful for

Business Users

David Stodder

Director of Research for Business Intelligence

TDWI

September 23, 2014

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Sponsor

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Speakers

David Stodder

Research Director,

Business Intelligence,

TDWI

Allen Bonde

VP, Product Marketing

and Innovation,

Actuate

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Agenda

Visualization: The age of beautiful data

Meeting the goal of improving decisions

Visualization and business intelligence

Meeting diverse user requirements

Best practices for visual data interaction and discovery

Where dashboards are headed amid technology changes

Visualization options: many choices

Reducing the noise and increasing understanding

Recommendations

Visualization: Seeing What Hides in Data

Graphics reveal data. Indeed graphics can be

more precise and revealing

than conventional statistical

computations. Edward Tufte

The 20 billion or so neurons of the brain devoted to

analyzing visual information

provide a pattern-finding

mechanism that is a

fundamental component in

much of our cognitive

activity. Colin Ware

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Credit: Stephen von Worley, www.datapointed.net

Geolocation of cell phone reports of dengue fever outbreak in

Lahore, Pakistan. Credit: MIT Technology Review

Confluence of Science and Practice

Human powers: We perceive meaningful

patterns, structures, and

outliers in what we see

Scientific focus: How we respond to graphical stimuli;

how we use memory to

process information

Common discourse: Media employs visual data

representation to explain

current events

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Credit: www.adinstruments.com

Cognitive Perspective on Visualization

Humans & Data: Visualization is the interface

between the human visual

system that finds patterns and

makes decisions and the

powers of data computation

Making sense of the data tsunami: One of the greatest benefits of data visualization

is the sheer quantity of

information that can be

rapidly interpreted if it is

presented well. (C. Ware)

Collaboration: People communicating with

computer visualizations

are much more cognitively

powerful; thinking occurs through interaction

between individuals, using

cognitive tools, and

operating within social

networks. (Ware)

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Enabling New Perspectives and Analysis

See what is unforeseen: Visualization allows perception of emergent

properties that were not

anticipated. The perception

of a pattern can be basis of

new insight. (Ware)

Exposing quality issues: Visualization often enables problems with the

data to become

immediately apparent; it

reveals things not only

about the data itself, but

about the way it is

collected. (Ware)

Data relationships: How are data objects linked or

related? Visualization can

make these more apparent

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Visualizations: Some Easy, Some Hard

Visualization as a sensory language

Understanding pictures without learning

Symbols that are hardwired into the brain; understood across cultures

Visualization as a learned language; learning curve

Diagrams: symbols based on social interaction

Semiotics : about how symbols convey meaning

What is meaningful to one is nonsense to another

Can be hard to learn, easy to forget

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Visualization: Goal is Decision Making

J.J. Gibsons Affordance Theory: That we perceive in order to act, to operate on the

environment; goal-directed

Top-down view of visualization: We do not perceive points of light; we

perceive possibilities for action

Performing operations: math ops, merging, inverting,

transforming, splitting into

components, etc.

Forming new kinds of data

Pattern perception: dividing regions into

simple patterns (e.g.,

same colors);

detecting motion

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Multiple Objectives Coming Together

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Context:

Addressing

the users role

Calibrating to

the users experience &

knowledge

Presenting

available data

accurately

Inspiring

good

decisions

and actions

To gain and keep the users attention

Visualization and Business Intelligence

Key to self-service trend: Visualization is essential to

making BI easier for

nontechnical users to consume

and interact with data

Shortening path to insight: What BI has always been

about; visualization accelerates

users progress

Business agility: Viz key to enabling data-driven decisions

But: Success depends on data; bad data = bad visualizations

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Key ROI Focus: Better Operational Efficiency

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Organizations want to use visualization to reduce time to

insight for all types of users in many different scenarios

From Data Visualization and Discovery for Better Business Decisions, TDWI Best Practices Report, Third Quarter 2013

Most Important Visualization Objectives

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Visualization: Diverse User Requirements

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View of visualization usage patterns in three key areas

Source: Data Visualization and Discovery for Better Business Decisions, TDWI Best Practices Report, Third Quarter 2013

Visualization & Display/Snapshot Reporting

Snapshots: Scheduled rather than requested ad hoc;

users want to personalize

based on roles

Visualizations must be accurate and consistent

KPIs and scorecards: Orienting users toward goals

and objectives

Can users or developers make the look more exciting using

fun visuals?

Drill-down flexibility: Critical

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Source: Claimcare.net

Operational Alerting: Avoiding Fatigue

Situations that demand immediate attention: watch

out for alert fatigue

Using color, size, animation, etc., flexible visualization can

help users prioritize and

recognize sources

Spotting trends and anomalies in event data streams

Time is of the essence: Real (or near real) time vital

Mobile devices: form factor a visualization concern

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Credit: www.catchpoint.com

Visual Data Discovery and Analysis

Fusion: Analytics, test-and-learn data exploration, and

advanced computation

matched with visualization

A visual path: data interaction through filtering,

comparing, and correlating

visual data relationships

Business data laboratory: Enabling exploration of who,

what, when, why behind

events and transactions

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Visual Discovery Best Practices

Guidance is necessary: Self-service and freedom

are important, but most

users need guidance

A blank slate with too many visual options can be

intimidating

Metadata matters: Common models,

hierarchies, dependency

mapping, etc., enable

users relate different data

sources and metrics

Big data access is often important: Viz helps users

cope with the data tsunami

Yet, limits to how much data can really be shown mean

that aggregation, chart

selection, and well-designed

dashboards are critical

Scale and performance: Ensure data infrastructure

support

In-memory and cloud are potential options

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Good Visual Data Interaction: Imperative

Too much is too much: Drowning users with data even if presented well is useless if users cant do what they need to

Goal: Get users beyond putting pretty pictures on numbers and toward more immersive data

experiences

Critical: Drill down, slice and dice, filtering, sorting and

modifying data, customizing

report items

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Sanctum, Rogue Pictures, 2011

Encouraging Storytelling, New Forms

of Collaboration Using visualization to narrate the

data story being told

Most visualization stories begin with some kind of question that orients

the viewer to the topic and context

within which the data is most

meaningful. Steele and Iliinsky

What data are we looking at?

In what time frame does the data exist?

What notable events or variables influenced the data?

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Dashboards: Bringing It All Together

Visual, role-based view of actionable information

Nexus of self-service BI and analytics

Performance mgmt: visibility via access to data-driven,

outcomes-oriented metrics

Integration at the glass: internal and external data,

metrics, content

Many types of dashboards and often many dashboards Credit: www.triadtechpartners.com

Source: www.nrel.gov

Old and New Visions of Dashboards

First-Gen Dashboards

Tabular reports with few and only simple charts

Limited number, variety of data sources

Limited methods of finding, interacting w/data

Dependent on IT developers to create and

modify

Tied to single tool or application

Where They Are Going

Libraries of chart types; drag-and-drop selection

Role-based, single view of data from multiple sources

Integration of search, advanced analytics tools

Self-service creation, preferably managed or

guided by IT expertise

Integrated view; seamless experience on mobile

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Visualization Options: Many Choices

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Heat map example

Scatterplot example

Bullet graph example. Credit Stephen

Few, www.perceptualedge.com

Gauges and dials example. Credit:

www.mockuptiger.com Sparklines example. Credit: www.edwardtufte.com

3D visualization example

Choosing Visualizations: Best Practices

Avoid clutter; no eye candy

Consider the audience: executive? A team?

Pay attention to context; emphasize

what matters

Aim for relevance; dont mislead or confuse

Step beyond convention but do so with purpose

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Source: Data Visualization and Discovery for Better Business Decisions, TDWI Best Practices Report, Third Quarter 2013

Recommendations Gauge where users are right now with data interaction

Are they using spreadsheets? Enterprise BI reporting? What role does data play currently in their decision processes?

Assess the learning curve: are visualizations more sensory or learned?

Make visualization part of effort to achieve BI/analytics democratization Visual can help nontechnical users who struggle to interact

effectively with data especially big data

Tools alone dont make it easy; remember context, role, purpose

Match users requirements to match the right capabilities Display, snapshot reporting, or scorecards?

Operational alerting?

Visual data discovery and analysis?

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Closing Recommendations Increase data interactivity with broader visualization

options and functionality But rather than give users a blank slate, ensure that they have

guidance, either through software or from IT developers

Data provisioning: Ensure you have a scalability and data performance strategy for visual discovery and analytics Consider expansion to the standard BI/DW architecture, such as

in-memory computing and cloud options

Dashboard clarity and relevance: Employ data visualization to reduce (not increase) confusion and

clutter and increase speed to insight

Match functionality with users decision processes; allow for personalization and customization; aim for single view

rather than dashboards for each app or (mobile) platform

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Thank You!

David Stodder

Director of Research for BI

dstodder@tdwi.org

(415) 859-9933

For a visual to truly be beautiful, it must go beyond merely being a

conduit for information and offer

some novelty.

When done beautifully, successful visualizations are deceptive in their

simplicity, offering the viewer

insight and new understanding at a

glance. J. Steele and N. Iliinsky

Beautiful Visualization: Looking

at Data through the Eyes of

Experts, J. Steele and N.

Iliinsky, OReilly Media, 2010

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Making Data Beautifuland Actionable

Allen Bonde

VP Product Marketing & Innovation, Actuate

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Computers like data

people like answers!

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What do you want to visualize?

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Insights for everyone, everywhere

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CLOUD ARCHITECTURE

BIRT iHub

Metrics Manager

BIRT Studio

Interactive Viewer

Dashboard

RDBMS, NoSQL/NewSQL, Hadoop, Cloud, Social Media, Enterprise Applications, Document Archives, Print Streams, Data Warehouses

Supporting all channels requires SCALE

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Follow the Crowd (open is better)

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BIRT Embedded in OEM and SaaS offerings

and other partners

One of the main reasons why we chose

Actuatewas the API structure and the

architecture. Being able to customize the

workflows, being able to customize the UI, and

how that was exposed to our customers was very, very important.

WHITE LABEL is key to embedding

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Your userswill decide!

helpful

Are you being?

relevant

engaging

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Learn more: www.actuate.com Follow me: Twitter.com/abonde

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Questions?

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Contact Information

If you have further questions or comments: David Stodder, TDWI dstodder@tdwi.org Allen Bonde, Actuate abonde@actuate.com

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TDWI Big Data Analytics Solution Summit

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Emerging Technologies 2015 Orlando, FL | December 7-12, 2014

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