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Unlock Value from Data Visualizations

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Title: Unlock Value from Data Visualizations


1
How to Unlock Value in Data Using Data
VisualizationsVIZ
Chaitanya Sagar CScs_at_perceptive-analytics.com
646.583.0001
2
Spreadsheet Solutions

Data Analytics
3
Our Services
Analytics
Spreadsheet Solutions
Data Visualizations Marketing Marketing Mix
Modeling Price Promotion Analysis
Catalogue Optimization
Segmentation
Web Analytics Churn
Analysis Risk Management Credit Risk
Management Liquidity Risk
Management Capital Allocation Analysis
Collateral Management Fraud
Detection Supply Chain Inventory
Optimization Demand Analytics
Distribution Network
Optimization Sourcing Analytics
Freight Lane Analytics Verticals
Consumer Packaged Goods Retail
Healthcare
4
Our Services
Analytics
Spreadsheet Solutions
Spreadsheet Applications Contract
Negotiation Litigation ModelingDecision Support
Tools
Dashboards Reporting Simulations Financial
Modeling
5
Location Strategy to Improve Effectiveness of a
Branch Network
perceptive-analytics.com/tag/case-study/
6
Reinventing Coupons Strategies for Successful
Coupon Campaign
perceptive-analytics.com/tag/case-study/
7
Financial Forecasting Tool for a Silicon Valley
Startup
Kina, Inc. is a hi-tech company based in Silicon
valley. The companys operations were growing and
wanted to track the cash flows in end-to-end
business process. The CFO of the company wanted
to project future cash requirements.
Cash Position Is the company investing or
accruing cash?
Net Sales How fast are revenues increasing?
Net Margin Is business profitable?
Avg. Selling Price Is the average sales price
picking up?
A comprehensive financial model which integrated
the working of different departments was built.
The model performed scenario analysis at various
levels of sales and inventory investments to
estimate the cash requirement. This model was
presented to the executive board of XYZ, Inc.
8
Questions?
  • Use ask-a-question feature in GoToWebinar

cs_at_perceptive-analytics.com 646.583.0001
VIZ
9
Which industry do you work in?
  • Retail and Consumer Packaged Goods
  • Health Care
  • Banking, Financial Services and Insurance
  • Information Technology / Consulting/Others

cs_at_perceptive-analytics.com 646.583.0001
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10
Which Function Do You Work In?
  • Analytics
  • BI
  • Sales and Marketing
  • IT
  • Finance/Operations / Human Resources

cs_at_perceptive-analytics.com 646.583.0001
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11
Overview
  • The need for visualizations
  • How visualizations help unlock value
  • How to build visualizations
  • -Purpose
  • -Design
  • Tools
  • QA

Pic y Horia Varlan
cs_at_perceptive-analytics.com 646.583.0001
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12
The Need for Visualizations
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Our Needs Outgrew Charts
  • More data!

cs_at_perceptive-analytics.com 646.583.0001
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14
Humans are Visual
  • Brain can absorb large amounts of information and
    find patterns (and deviations!)

Pic by Dan Foy
cs_at_perceptive-analytics.com 646.583.0001
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15
?
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Mind is a Pattern-Matching Machine
Edward De Bono Mechanism of the Mind (1969)
cs_at_perceptive-analytics.com 646.583.0001
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23
cs_at_perceptive-analytics.com 646.583.0001
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24
Anscombes Quartet
25
How are the Data Sets Different?
  • All four data sets are identical
  • Distribution is different
  • Median and Mode could be different
  • Not Sure

cs_at_perceptive-analytics.com 646.583.0001
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26
Statistics May Hide Something
cs_at_perceptive-analytics.com 646.583.0001
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27
Statistics and bikinis show a lot, but not
everything.
  • Toby Harrah
  • American baseball player

cs_at_perceptive-analytics.com 646.583.0001
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28
Where do Data Visualizations Fit in Data
Analytics Process?
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29
Where does Data Visualization Fit in Data
Analytics Process?
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30
How Visualizations Help Unlock Value
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31
Make Sense of Vast Data Quickly
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Make Sense of Vast Data Quickly
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33
Elicit Questions You Did Not Ask Before
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34
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35
Sample Responses
  • _at_RNTata2000 in all democracies there is a gap on
    what ple want and what politicians r
    delivering,they r not doing the right thing,
    lobbying?
  • _at_bangaarm _at_RNTata2000 Budget 2012 This year is
    Tax Holiday. No income tax on your earnings. This
    is to bring back all the black money to India
  • _at_sri_v22 _at_RNTata2000 1. Kill corruption 2.
    Electoral reforms so that honest ple can get into
    politics 3. Media activists should increase
    their role
  • _at_joseaaa _at_RNTata2000 Can't be articulated with
    140 characters. Quality education for the masses
    is magic potion that can address most of the
    problem.
  • _at_dharmeshsharma8 _at_RNTata2000 Could we have your
    view on this topic?

cs_at_perceptive-analytics.com 646.583.0001
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Elicit Questions You Did Not Ask Before
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37
Discover New Data Relationships
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Discover New Data Relationships
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39
Show Others What You See
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40
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41
Show Others What You See
http//guns.periscopic.com
42
How to Create Visualizations
cs_at_perceptive-analytics.com 646.583.0001
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Analyst
Data
Tool
Insights
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Analyst
Data
Tool
Domain / Situation
Imagination
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45
Purpose
Design
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Purpose
Pic by Mervi Eskelinen
Tasks
Audience
Answers
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Guidelines
  • Understand your goals
  • Determine the most important dimensions of your
    data
  • Determine key data relationships
  • Show data close to reality e.g. maps, time lines
    etc.
  • Choose encoding wisely Function first, suave
    next
  • What questions do you want answered?

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Design

Pic Ecotrust Canada
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49
Visual Encoding
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50
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What Do You Think About This Chart?
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53
Whats Wrong with this Chart?
  • Too Big
  • Poor colors
  • Nothing wrong, looks good
  • Its just wrong
  • No comment

cs_at_perceptive-analytics.com 646.583.0001
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(No Transcript)
55
Edward Tufte
cs_at_perceptive-analytics.com 646.583.0001
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56
Thousands
Thousands
57
Avoid Chart Junk
Thousands
58
Avoid Chart Junk
Thousands
59
Maximize Data Ink RatioData-ink/Total ink used
Maximize Data Density ( entries in data
matrix)/(area of graphic)
60
Colors
cs_at_perceptive-analytics.com 646.583.0001
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61
Colors
  • Create Color Harmony

cs_at_perceptive-analytics.com 646.583.0001
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62
Ideas for Color Harmony
  • Analogous

Complementary
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63
ColorBrewer2.org
64
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Tools
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66
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67
cs_at_perceptive-analytics.com 646.583.0001
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68
Resources
  • Designing Data Visualizations (Noah Iliinsky,
    Julie Steele)
  • Visual Encoding
  • complexdiagrams.com/properties
  • richardbrath.wordpress.com
  • Edward Tufte
  • edwardtufte.com
  • D3JS.org
  • Processing.org
  • Principles of Visualization Design
  • D3 Visualizations

cs_at_perceptive-analytics.com 646.583.0001
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69
QA
cs_at_perceptive-analytics.com 646.583.0001
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70
Your Feedback on this Webinar
  • Below Expectations
  • Met Expectations
  • Above Expectations

cs_at_perceptive-analytics.com 646.583.0001
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71
Thank you!
cs_at_perceptive-analytics.com 1.646.583.0001
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