data visualization: the what, the who, and the how (287772413)

8/20/2019 Data Visualization: The What, the Who, and the How (287772413)

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Top 3 Visualization of All Time?



March on Moscow – Charles Minard



GapMinder - Rosling



ondon Cholera Map – !ohn "now #$%&'(



O%%ortunities in the Use of $ata Visuali&ation

Objectives:

)n order to get people to use the tools

and ma*e data dri+en decisions, it is+er important the are comforta.lewith the tool/ "imple tools ma*e theadoption of such tools easier in the

enterprise/ Thus, the results will dri+ethe performance of the organizationto a higher le+el/



User Community

+ $evelo%ers and Programmers

+ on-$evelo%ers

Point to note. /hat 0or!s 0ell for technically

savvy develo%ers may not 0or! for faculty or staff

0ithout those same credentials1



on-Technical Solutions+ $ata /ra%%er

+ #a0

+ Infogram+ Tableau

Point to note. These %roducts can ta!e basic data and

visuali&e it in charts, gra%hs, and in some cases

geogra%hical ma%s1 These %roducts can be used by faculty

and staff 0ith little intervention from IT, as long as they have

a basic familiarity 0ith s%readsheet data1



$evelo%ers+ Oracle suite of O2I(( 3Oracle 2usiness Intelligence (nter%rise

(dition4 has been very successful for CSU

+ Cognos 3I254 is another tool that is very %o%ular for develo%ers

and has been used by USG central office

+ $6 37or $ata $riven $ocuments4

+ 7usion Charts

+ Chart 8s

+ Google Charts

Point to note. 'el%ing a %rogrammer or develo%er learn ta!es time

through training1 If he or she can learn by shado0ing a consultant

or an e)%erienced develo%er, learning ha%%ens 9uic!er 1



#eality of 'igher (d (nvironment and /hy$ata Visuali&ation 5a!es Analytic (asy:

+ As!ing a $ean or Chair to use O2I(( is li!e as!ing a math

ma8or to %erform brain surgery1 2oth e)am%les may get the 8ob accom%lished, ho0ever, both 0ould be a ;bloody; mess1

+ In addition, many times the ;0ait; for a develo%er to %rovide

the data in a dashboard ta!es too long for these non-

technical grou%s1 They 0ant the information no01

+ Once they 3functional users4 get the data, they as! more

9uestions since they don<t !no0 0hat they really 0ant or are

loo!ing for=



T0o %rimary design goals su%%orted through

$ata Visuali&ation

+ $iscovery and ()%loration

> /hat story is the data telling you

> Identify %atterns and e)ce%tions

+ $ecision-ma!ing

> Com%are, contrast, choose

> ()%lain, ma!e a %oint, decide



$ata Visuali&ation Strategies. Visual

Analytics Tools Su%%ort $ata $iscovery

()am%les. 'eat ma%s, 0hat-if modeling, %redictive modeling, charts



$ata Visuali&ation Strategies. Visual

#e%orting Tools Su%%ort $ecision-ma!ing

()am%les. $ashboards,

scorecards, PIs



Ti%s and 2est Practices

+ $ata is still the !ing

+ no0 your re9uirements

+ #ecogni&e your audience

+ 2alance s%arsity and density

+ Prototy%e-test-iterate

+ ?everage tem%lates > standard loo! and feel

+ Use color for distinction and selection

h 0 i i f A i



0sing 1ata Visualization

To communicate 2resent more clearl or more forcefull

than would .e accomplished with tet orta.les

Reports, dash.oards, infographics, etc/

To disco+erAllow us to see what would .e di4cult or

impossi.le to see if not presented in auseful +isualization

Realm of research .ut mo+ing into themainstream

Can same +isualization ser+e .oth

he 0ni+ersit of Arizona

A5 R A t 72 th 0 i it f A i



A5 R Actua s72ro ect ons +s/Goals


h 0 i it f A i



Research 9 +s/ "C: Taughthe 0ni+ersit of Arizona

h 0 i it f A i



Curricular ;low – ;orwardhe 0ni+ersit of Arizona



C)V)TA" <AR=)=G, )=C/ -- C6=;)1<=T)A )=;6RMAT)6=

;or FTIC FT Freshman in their First Term, .oth "AT andACT Math scores ma*e the list with clear tipping points for.oth> "AT Math #&&( and ACT Math #@(/

UA I N S I G H T S

"tudents in thissegment with ACTMath scores greaterthan @ also persist ata rate $ percentagepoints higher than

those .elow @

"tudents in thissegment with "ATMath scores greaterthan && persist at arate $ percentagepoints higher thanthose .elow &&




1eri+ed )mplicit "ocial =etwor* Tied to Retention




http>77dash.oardsp/com7dash.oards7'B7intuiti+e-dash.oard-design-reattenti+e-+aria.les

Introduce Pre-Attentive Variables



Avoid Pie Charts==

http>77www/perceptualedge/com7articles7+isual.usinessintelligence7sa+ethepiesfordessert/pdf



/hat $o @ou Thin!:



Avoid Pie Charts * Color Usage

Color 5lindness in the General2opulation



Initiate Infogra%hics



Duestions

"hould we tr to suppl data+isualization tools centrall?

"hould we tr to support good

practices around data +isualization?Ehat organizational unit#s( would .e

responsi.le?

Eh did our information sa++ deansresist our presenting informationgraphicall?

:ow do we connect the research




uestions * Ans0ers:

# d d #



31

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"ources for )nspirations>



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data visualization: the what, the who, and the how (287772413)

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