the art technique of data visualization

The Art & technique of Data Visualization

Welcome to the webinar on

Presented by

&

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

Why BI projects fail?

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.

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

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

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?

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

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

STEVE JOBS

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

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

Is this for the CEO or Production head?

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

One more way to do it..

KPI Map

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

Demo – (Alerts) Disbursement Dashboard

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

Demo – Excel Illustration

Demo – NPA Analysis

Personalization

Personalization

Personalization

Personalization

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

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

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: info@ellicium.cominfo@compulinkacademy.com

Stay tuned for our next webinar on “Text Analytics”

Let’s hear it from you