Data Visualization
Data
visualization is a general term used to describe any technology that lets
corporate executives and other end users “see” data in order to help them
better understand the information and put it in a business context. It is used
to communicate data or information by encoding it as visual objects (e.g.,
points, lines or bars) contained in graphics.
Business Vignettes and Methods of Presentation
Human Resource Management
Human
resource management include data management of employment related actions such
as recruitment, promotion, classification, compensation, performance, training,
etc. Some important metrics related to human resource management are headcount
of employees in each department, number of employees in the company by year,
number of employees by salary, payroll breakdown in various departments, etc.
To represent these metrics some of the common presentation methods are
horizontal and vertical bar charts, pie charts, doughnut charts, line charts,
etc.
To represent human
resource (HR) data, bar charts seem the most appropriate to me. This is because
HR data can mostly be represented along two axes. For example, data can be plotted
against number-year, cost-year, department-number, etc. Visualization using bar
charts looks simple and clean, yet informative.
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| Bar chart showing HR data |
Financial Services:
Banking
Banks have access to
more customer information than businesses in any other sector, and it is vital
to effectively leverage information assets. Currently, transactional data
remains one of the keys areas of focus for financial institutions. Analyzing
transactions can uncover powerful insights into customer needs, preferences and
behaviors. Transaction data can be represented by a number of different charts
since each time it may have different attributes to represent. For example,
while representing number of transactions across different credit institutions,
we can use the simple bar chart. Whereas, to represent complex data such as detailed
transactional activities across amount and time, we may use something as
complex as an area chart.
To ease visualization, I
believe it is better to show information in multiple charts instead of cramming
all information into one chart. A combination of pie chart, stacked charts and
line charts can be used to analyze different transactions across different
attributes. These chart types are simple and easy to understand rather than
complex charts like area charts.
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| Pie charts and Stacked charts showing transactional data in Banking domain |
Transportation
To keep up with the demands of the information age,
transportation firms must do more than simply move passengers or shipments from
point A to point B on time. Customers demand constant real-time visibility and
increased self-service. Employees must provide just-in-time service via a
combination of traditional tools and mobile devices. Managers need the business
insight to optimize schedules and routes, hedge fuel costs, create the right
marketing offers, set competitive fares and rates, and identify and retain top
employees.
Based on the type of data being shown, we can use various
type of charts in the transportation domain. This may include bar chart, pie
chart, heat maps, bubble chart, line chart, doughnut chart and other
geographical maps.
In my opinion, it all depends on the type of transportation
data that you want to show. Depending on the need, one can choose from bubble chart, heat maps and
geographical maps. For example, if we want to see which city has the most
number of public transportation routes available, we might choose a bubble
chart. But if we want to view traffic distribution across different areas, we may
use geographical maps.
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| Transportation data on geographic map with numbers |
 |
| Bubble chart showing transportation data in different cities |
Sources:
Wikipedia
Google images
