the art technique of data visualization

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Page 1: The art  technique of data visualization

The Art & technique of Data Visualization

Welcome to the webinar on

Presented by

&

Page 2: The art  technique of data visualization

This webinar aims to cover the following

1 Why BI projects fail?

2 What is Data Visualization?

3 Who needs Data Visualization?

4 The 3D Framework

5 Lets hear it from you

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Why BI projects fail?

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Data Visualization - Defined

Data Visualization is the art and technique of representing data in a graphical and pictorial format

It is the moment of truth resulting from any DWH / Big Data initiatives

Why is it important?

Human Brains

Are equipped to perceive

meaningful patterns, outliers, and

structures to form a judgment.

Decision Making

No 1 priority : support decision

making.

Adding value to the volume, variety

and velocity of data that is

generated and processed.

Communication

Inform : What & Why

Educate : What If, What Next &

What Can

Collaborate : Who, What Else & How

Exactly.

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Data Visualization Eco-System

Who needs Data

Visualization

Regulators

Customers

Suppliers

Analysts

Why?

Decision Making

Business Users

IT Executives Operational

Efficiencies

Regulatory Compliance

Mind Share

Progress in value chain

Monetize existing data

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TDWI research : Based on answers from 388 respondents

77% areBusiness executives and management

58% areBusiness Analysts

55% areDepartmental Managers

IT Executives

Data Analysts or Scientists

Front line employees

38%

37%

25%Operations / SCM

Customers

Partners & Suppliers

24%

14%

8%

Primary users of Data Visualization

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Who in your organization develops & deploys Visualization?

The gap is fast reducing.. Thanks to the New self-service and personalizationTechnologies.

TDWI research : Based on answers from 388 respondents

Business executives are the largestConsumers of Data Visualization

This era is characterized by business analyst / users making and also consuming their own data through visualizations..

Can the IT developers make themselves more relevant?

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Our 3D Framework

DATA

Data Accuracy Visual Querying Multi-dimensional Personalization

DESIGN Know your

audience Personalization Collaboration

DISCOVERY

Keep it simple HighlightBU

SIN

ES

S K

NO

WLE

DG

E

DATA VISUALIZATION PRODUCTS

INFO

RM

ATIO

N D

ELI

VE

RY

ME

THO

DS

ComponentsPrinciples

Enablers

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You’ve got to start with the customer experience and work back toward the technology – not the other way around

STEVE JOBS

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Know your audience

Challenges

Lack of participation from business users

Best Practices

Conduct business workshops to finalize the requirements document

Low / No awareness about the business or domain

Data Visualization created in silos

Make sure you understood the data that is required

Get a sign off first on the design and layout

Break it down to individual parts / graphs / quadrants and take a sign off

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How not to do it – CEO Dashboard for a manufacturing co.

Is this for the CEO or Production head?

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How best can it be done – CEO Dashboard for a manufacturing co.

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One more way to do it..

KPI Map

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Highlight

Challenges

Limited space for utilization

Recommendations

Color : Contrast

Limited or Excess data to show

Color : Intensity

Position Motion Alert

Length Width

Size Shape

Harvey Balls

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Demo – (Alerts) Disbursement Dashboard

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Visual Querying

Challenges

How many drill-downs?

Best Practices

Information relevance

How to showcase correlations?

Sequence of clicks

How to avoid information chaos?

Present the Metadata

Parent child relationship

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Demo – Excel Illustration

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Demo – NPA Analysis

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Personalization

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Personalization

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Personalization

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Personalization

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Choosing the right visualization: few examplesVisualization Type Description Chart Type

Comparison Many Items Horizontal Bar Chart

Comparison Over time: Many periods Circular Area Chart

Comparison Few Periods: Many Categories Line Chart

Relationship Two Variables Scatter Chart

Relationship Two + Variables Bubble Chart

Distribution Few Data Points Column Histogram

Distribution Three Variables 3D Area Chart

Composition Few periods: Changing over time Stacked column chart

Composition Static: simple share Pie Chart

Composition Universe of content Tree Map

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Repository of best practices

Avoid Scroll bar as far as possible

Facilitate definition of the visualization

Convert decimal points to a perfect integer

Make navigation really easy for the end user

All axes should be properly labelled

Good idea to show data quality % in the visualization

Avoid using special characters or short forms for labels

While displaying bar charts, order data in descending order

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Interested in knowing more?

Interested in knowing more about our 3D Framework for Data Visualization & how it can add value to your clients?

Then, our dedicated training workshops on the “The Art & Technique of Data Visualization” is the best forum to learn more practical and industry accepted methods on improving data visualization.

Contact: [email protected]@compulinkacademy.com

Stay tuned for our next webinar on “Text Analytics”

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Let’s hear it from you