ITAB Module 5 Data Visualization and Visual Analytics

vision

is by far our most powerful sense

data visualization

• there is an amazing connection between human visual sensors and the brain

• humans have an extraordinary visual capacity to detect patterns

visual perception

to display data effectively we must understand a bit about _______.

visual perception

• how many nines are in this matrix?

• can you see any pattern in this table?

• can you see any pattern in this line graph?

anscombe’s quartet

• four distinct datasets

• each with statistics properties that are essentially identical

• nearly identical correlation and regression line

anscombe’s quartet

• four distinct datasets

• each with statistics properties that are essentially identical

• but when plotted, they suddenly appear very different

anscombe’s quartet

______ suggested the combined use of graphs and statistics methods in data analysis

data visualization

is essential for:

• data exploration and understanding

• communicating data

• making better decisions

understanding

people make better decisions when they’re based on ______. for information to be understood, it must often be presented in visual form because patters, trends, and outliers require a picture for the human brain to see and comprehend

data visualization

is the graphical display of abstract information for sense-making or data analysis for action

data visualization

its goal is to visualize data in a way that leads to understanding

data visualization

_______ is a fundamental product from the visual analytics process

common types of graphs and charts

• bar chart

• stacked bar chart

• line graph

• area chart

• pie chart

• scatterplot or scatter graph

• bubble scatter graph

• bullet graph

less common types of graphs

• box-plot graph

color scheme types and combinations

• qualitative

• sequential

• diverging

• binary

qualitative

colors do not have a perceived order

sequential

colors have a perceived order and perceived difference between successive colors is uniform

diverging

two sequential palettes starting from a common color

graph design principles

• Show / emphasize the data

• Maximize the data-ink ratio

• Decluttering: erase non-data ink as much aspossible.

• Consider removing: Border, Grid lines, Backgroundshading, Axis (if you plan on labeling the datapoints)

• Erase redundant data ink

• Use of color to add emphasis

• Revise, iterate, edit and get feedback from others

graph design rules

• Keep it simple and avoid flashy special effects

• Title the chart clearly to convey a purpose

• Specify the units of measurement on the x- and y-axis

• Add legend when encoding data using symbols,shading, and color

• Label each part of the chart including legend

• Add annotations if necessary, but avoid adding textsand annotations over the chart area

• Specify the data source

visual analytics

is the science of analytical reasoning supported by interactive visual interfaces

visual analytics

it encourages visual thinking by leveraging the powers of human perception

visual analytics method

allow people to combine:

1. human flexibility, creativity, and background knowledge

2. + IT capacities for data storage, processing, and visualization

3. = to gain insight and make well-informed decisions in complex problems

the analytic process

1. the research question - situation/problem

2. formulation of the conceptual framework

3. identification of data sources

4. create the analytic plan - methods

5. conduct analysis & interpretation of results

6. communicate results and findings - visualization and storytelling

7. propose interventions - actions for improving the situation/problem

the cycle of visual analytic

When people are exploring andanalyzing data, they enter into an iterative and non-linear cycle of

1. data acquisition,

2. selection of visual structures

3. instantiate data views(graphs, visual forms)

4. analysis and synthesis,hypothesis building

5. sharing and re-examination

where at any point they mayneed to skip steps, back-up,seek additional data, or evenstart over

rigorous

a meaningful data visualization is a result of a ____ data analysis

libraries

• Libraries for adding charts and visualization capabilities to applications

• Required programming or coding. Suitable for software developers

• Use Programming Language directives to connect to data sources

web-based tools

• Visualization tools on the web

• Easy to use, no programing required

• Datasets should be upload. Suitable for small-medium datasets

data analytics and visualization platform

• is an enterprise-class (complete) solution that provides the tools and methods for:

1. connect to most of the DBMS standards (SQL, Web services, local files, etc.)

2. to data exploration and visual analytics,

3. creation and design of data visualizations and dashboards, and

4. capability for team collaboration and content sharing, and dissemination

• None or minimum programming required

• Self-service approach, empower business users.

dashboard

is a collection of resources asembled to create a single unified visual display