Lynn has spent over 20 years designing and building software for a variety of industries including biotech, oil & gas, healthcare and finance. She has spent a good deal of her career visualizing large data sets on the web

Product Marketing Specialist, DataStax

Gehrig has years of experience fostering open-source communities; helping others learn how to build and scale cloud applications.

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DataStax provides data management for cloud applications.

© 2017 DataStax, All Rights Reserved. Company Confidential

Cube & Fixed Dimensions - easier to zero in on what’s important to the user!

Filter value = Slicing: Reduce dimensionality by selecting a single row along one dimension.

Filter range / Zoom = Dicing: Focus on a sub cube

Aggregate = Roll-up: Reduce dimensionality by summing one dimension

Detail on demand = Drill-down: Subdivide to create more dimensionality.

Field selection = Pivot: Rotate data cube

● Degree● Betweenness● Shortest Path ● Clustering, Communities● Similarity● Dependency

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DataStax Enterprise Graph

• Real-time graph database• Manage complex and highly connected data• Discovering commonalities and anomalies in data• Stored as Cassandra tables behind the scenes

Indexing& Search

StreamingAnalytics

Graph

BatchAnalytics

DataStax Enterprise Multi-Model/Mixed Workload

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Powering cloud applications

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Effortless scale

Always-on● Designed to handle any failure,

no matter how catastrophic.

● Take advantage of every opportunity.

● Focus on what matters most to you.

Instant insight● Built into your application to create

actionable, modern experiences.

Copyright of Shell International RESTRICTED 15

Successful Products Result from Many Elements Working Together

VISUAL DESIGN

CONTENT

INTERACTION DESIGN

INFO ARCHITECTURE

FUNCTIONALITY

USER AUDIENCE

USA

BIL

ITY

USE

FULN

ESS

Who

What

How

…

Find the gapWhat users

think will bridge the gap

How can data bridge the gap

How do we present the

bridge

Design & test assumptions

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Copyright of Shell International RESTRICTED 20

Problem & User Identification Lays Foundation for All UX Design

VISUAL DESIGN

CONTENT

INTERACTION DESIGN

INFO ARCHITECTURE

FUNCTIONALITY

USER AUDIENCE

USA

BIL

ITY

USE

FULN

ESS

What

Who

TODAY FUTURE

Images courtesy of: Marketingdistillery.com / JohnDeere.com

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Microsoft 2014; Stephen Few, Signal 2015; http://www.ifp.illinois.edu/nabhcs/abstracts/shneiderman.html

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1s

RAM Cache

CPU

OutputProcessor

MediaProcessor

Video Buffer

Mic Buffer

Camera

Long-Term Memory

Size: unlimitedDecay: never

Working Memory

Size: 7 chunksDecay (1): ~100 sec

Decay (1+): ~5-30 sec

Cognitive ProcessingCycle: ~70ms

Motor ProcessingCycle: ~70 ms

Perceptual Processor

Cycle: ~100 ms

Visual Image Store

Size: ~17 lettersDecay: ~200 ms

Auditory StoreSize: ~10 tonesDecay: 1500 ms

EyeCycle:

~250ms

Narrow window & worse with distraction!

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User sign posts

Copyright 2015 Expero, Inc. All Rights Reserved 8/11/2015

Applying Dominant Dimension Method - Even big data can be small.

Copyright 2015 Expero, Inc. All Rights Reserved 8/11/2015

Applying Dominant Dimension Method - Even big data can be small.

Copyright 2015 Expero, Inc. All Rights Reserved 8/11/2015

Progressively Disclose Using Dominant Dimension + Entity

Dominant Dimensions: Time + (Health) Frequency

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Copyright 2015 Expero, Inc. All Rights Reserved 8/11/2015

Progressively Disclose Using Dominant Dimension + Entity

Lense Tool:Filter by primary entity (sensor location)

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Dominant Dimensions: Time + (Health) Frequency

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Copyright 2015 Expero, Inc. All Rights Reserved 8/11/2015

Use Progressive Disclosure to Reveal Detailed Data

Sensor Detailson Demand

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Dominant Dimensions: Time + (Health) Frequency

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Lense Tool:Filter by primary entity (sensor location)

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ENGINEERING USERS

Good Charts

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Tensor Flow - neural net

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** Tight integration for easy pivot between map and node

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Treatment Protocols (Graph) Population Health Data Medical Records Data

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Idea Illustration View care plan events over time Subway map

Standard Visualization View care plan events over time (frequency) Calendar heatmap, data tables

Idea Illustration View treatment protocol by disease state Flow diagram

Standard Visualization Population Health data (trends) Line charts, data tables

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Treatment protocols

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TYPICAL REPEAT 2 - 4X (4 - 8 Weeks)