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Contextual Visualizations

The popularity of Infographics has not declined. Its been around for many centuries; in fact Wikipedia has made references to the Infographic created describing the sun’s rotation pattern done by Christopher Scheiner pegged at year 1626. The old infographics were all obviously created by hand.  The last couple of years have made Infographics popular because of a combination of many trends – Data has exploded, people just don’t have time, computing power has exponentially increased, kids out of school can pick up a graphical package and create a story. Those are the driving factors for Infographics popularity. Social networks and sharing just add fuel to the popularity fire.

There is one thing though which hasn’t changed in a while. Almost all the data visualization elements created in the current versions of Infographics are a static slice of the data. This is where you start wishing – this is cool BUT I wish they could tell me more about THAT or THIS data element. At this point, you don’t have a choice and you  need access to the raw data and an analytic reporting tool.  We, at SecondPrism, didn’t want to lose the rich visual storytelling data visualizations of Infographics and neither did we want to lose the filtering and analytics.  We came up with this concept of Dynamic Infographics.

Infographics for Dimension Attributes

Dimensions describe the objects involved in a data analytics effort. Dimensions correspond to people, items, or other objects. For example, customers, employees, items and companies are dimensions if we consider a business scenario. We decided to tackle some key attributes of these dimensions.

For example, for people, we have these prominent quantitative attributes :

Gender

female

Age

Age center

Income

icon-dollar

house

Education

university

Marital Status

Married

 

Separated

Marital center

Type of Job (Full Time, Part Time)

employed-tie

 

 

If you consider behavioural attributes (called facts in the data world) for people, here are some :

Money Spent/ Saved

Money spend-saved

Hours Worked/ Saved

Time spend-saved

Emotions Exhibited

Emotions

Likes/Dislikes

Like-dislike

For companies, similar attributes apply :

Type of Business (Private, Public, Non-Profit etc.)

Size

Size

Years in Business

Years in Business

Number of Employees

Number of employees

Types of Services

Type of services

Types of Products

Type of product

Types of Promotions

Types of pomotions

Location(s)

If you consider behavioural attributes for companies, these are some :

Sales

Sales

Quality of Service/Product

Quality of service-product

Satisfied Customers

Satisfied-Customers

Marketing Effectiveness

Marketing effectiveness

And if you move on to items and products, similar attributes apply :

Type of Product

Type of product

Size of Product

Size of product

Color

Colors

Locations where manufactured/sold

Location

The power of dynamically adjusting these key visual elements when the underlying data changes because you either applied filtering or an analytical model is what Secondprism does best.