Overview

  • In today’s world where people are inundated with more data than they can process, data visualization plays a very important role as a crucial means through which information flows to the decision-maker
  • In this article we will approach data visualization in a holistic way, beginning with general considerations and evolving to specific data presentation considerations
  • Data visualization helps people understand the significance of data by placing it in a visual context. Patterns, trends and correlations can be exposed and recognized easier with data visualization. Data visualization facilitates managers to understand the concept, leads to new insights and one can go down to any level of the data by slice and dice of visualizations.
  • One can understand the data very clearly through visualization. Visualization of data suggests us the areas for correction. Also gives insight about customer’s ever changing behavior, helps in proper promotion and placement of product and facilitates to predict sales trends.
  • All the organizations can use BI visualization to have deeper and meaningful insights from their huge data to take appropriate decisions to improve business.

Understanding Type of Audience

Any Data Visualization needs to start with an audience in mind. What are their information needs? What do they already know? What are their experiences and prejudices?

Audience could be broadly categorized into two groups:

  • Power Users: Who would prefer to explore the data on their own (Exploratory)
  • End Users: Who would prefer pre-defined dashboards to be presented to them (Explanatory)

End Goal

Setting the goal should include determining whether the data visualization process will be exploratory, explanatory, or a mixture of both.

Design Considerations

Providing actionable insights, meeting user needs, and maximizing the user experience is at the heart of Data Visualization and hence the core of design.

Design Considerations in Data Visualization


Quality of Data

Visualizations need to tell a story. The success of Data Visualization depends on the quality of the data and the visual display.

  • Accessible Trustworthy Data
    • The data should be accessible with modest effort from a source that people trust.
  • Metrics Management
    • People in the organization recognize what the metric means and have a common interpretation.
  • Transparent, Simple Calculation
    • How the metric is generated and calculated should be known and easy to understand.
  • Actionable
    • Required action should be clear when the metric goes up, down, flat or off-target.

Understand complex/large datasets
Complex data generated by the organizations can be viewed critically by the managers through graphical and pictorial representations. Organizations can have insights to initiate appropriate measures to improve business as it would be much easier to analyze data through visualizations.

Huge amounts of data from various sources can give better analysis when presented graphically. KPIs can easily be measured and understood.  One can visualize business and market trend through visualizations which gives decision makers an upper hand over competitors.

Share the insights

The insights learnt from the visual analytics can be passed to other users down the line for better and effective implementation of strategy.

Types of Data Visualizations

Data can be represented through various types of visualizations to the users to effectively showcase and analyze data. Provides drill down facility to go to any level of the data.

Types of Data Visualizations

Bar chart –

A bar chart is a way of summarizing a set of categorical data. The bar chart displays data using a number of bars, each representing a particular category.

The height of each bar is proportional to a specific aggregation. The categories could be something like an age group or a geographical location. It is also possible to color or split each bar into another categorical column in the data, which enables you to see the contribution from different categories to each bar or group of bars in the bar chart.

 

Line Chart –

Line charts are used to display information as a series of data points connected by straight line segments on an X-Y axis. Line charts are useful in knowing the changes over a period of time.

 

Combination chart –

The combination chart is a visualization that combines the features of the bar chart and the line chart.

The combination chart displays the data using a number of bars and/or lines, each of which represents a particular category. A combination of bars and lines in the same visualization can be useful when comparing values in different categories, since the combination gives a clear view of which category is higher or lower. An example of this can be seen when using the combination chart to compare the projected sales with the actual sales for different time periods.


Pie Chart –

Pie chart is divided into sections to indicate a numerical proportion. Each section expresses its quantity through the size in proportion to other sections. Total pie chart tells us that all sections proportionally correspond to the quantity they represent.


Area Chart –

Area charts are used to show how individual parts make up the whole of something

 

Bubble Chart –

Bubble chart represents a numerical value visualized as circular bubbles and different colors are used to indicate different categories.

 

Scatter Chart –

Scatter visualization is used to see correlations and two sets of variables are plotted as data points on X and Y axis.

Funnel Chart –

Funnel chart is used to visualize the phase wise progressive reduction of data. Data in each of these phases indicates different portions total data.


Pyramid Chart –

Pyramid charts are used for data comparison based on thickness of the layers to represent relative values.


Radar Chart –

Radar chart is useful in plotting multi variation data in the form of a two-dimensional chart of three or more quantitative variables represented on axes starting from the same point.


Polar Chart –

Polar charts are used for displaying multivariate observations with number of variables in the form of a two-dimensional chart.


Wind Rose Chart –

Wind Rose chart is useful to present any directional information, or information that is cyclical in nature.


Map Chart –

Maps data lets you visualize data on a map and share it with others in one easy step.

You can map your customers, map economic data, map environmental data, or anything that has latitude, longitude, a coordinate, ZIP code or postcode. Try our web-based mapping software and see your own information placed onto a map.

Gauge Chart –

Gauge charts are used to measure KPIs.

 

Spark line Chart –

Spark line charts used for showing many trends at once for showing variation in a simple way


Heat map –

Heat maps are well-suited for visualizing large amounts of multi-dimensional data and can be used to identify clusters of rows with similar values.

 

Text Chart –

Table presents the data as a table of rows and columns, and is used to see details and compare values.

By clicking on a row you mark it, and by dragging the mouse pointer over several rows you can mark more than one row. One can sort the rows in the table according to different columns by clicking on the column headers, or filter out unwanted rows by using the filters.

 

Trellis –

Trellis visualizations enable you to recognize similarities or differences between different categories in the data.

 

Having the right tool to analyze the data through the power of visualizations drives the success of any organization. Getting the right insight through the right visualization at the right time is the secret sauce for seeing increase in revenue and profits for an organization.

 

About BIRDonCloud

BIRDonCloud is a highly secure and self-service based business cloud solution for your business intelligence, reporting and data analytics. BIRDonCloud provides a simple, flexible, & intuitive user interface with drag and drop features, powerful drill-downs, pivots, storyboards, visualizations, collaboration, embedding, scheduling, predictive analytics and elastic in-memory capabilities that work across all devices.

BIRDonCloud provides SaaS, On-premise, and Hybrid deployment options.

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