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Data Visualization Basics For Dashboards
Part 1

by Huzefa Johar, Content Developer, FusionChartsTuesday, March 9, 2010

In simple terms, a dashboard is a software application that retrieves an organization's data and presents it in a way that makes it easier to monitor and control business processes.  Since a dashboard displays information in a way that makes it easy to spot anomalies, managers are instantly alerted when something isn’t functioning in the intended way.  In fact, there have been several instances where dashboards have helped to avert problems long before they could manifest.

An important fact about dashboards is that they are multi-layered applications displaying data across three hierarchical layers. The top layer of a dashboard presents a comprehensive summary of data and therefore it is called the summary view.  If the user needs additional information s/he can navigate to the next level which is called the multi-dimensional view.  In the multi-dimensional view, the user can see additional data and at the same time manipulate the data for the purpose of analysis.  The bottom layer in the hierarchy is the detailed view layer where the user can see details of individual transactions.  In the language of business intelligence (BI), the term "drill down" is used for denoting an action that helps the user move from the summary view down to lower-level views.

Layered presentation of data is an effective way of providing information because people do not require all the data at one time.  What they need is summarized data with an option to access  detailed data only when it is needed.  Most dashboard users work from the summary view, as this  enables them to simultaneously monitor a wide range of business processes.  The summary view  is  therefore the most crucial aspect of a dashboard application.  It must be noted that although dashboards are built by programmers, conceptualizing a dashboard is more of a business analyst’s job.  A thorough understanding of business processes and knowledge of data visualization  methods is all you need for conceptualizing the front end of your dashboard application.  This tutorial will help you gain an in-depth understanding of the data visualization elements that are  incorporated into a dashboard.

Why Is Data Visualization Crucial To Dashboards?

Data visualization is a technique of turning data into information by via visually recognizing patterns and trends.  In other words, data visualization is all about representing data graphically.   Data visualization elements such as charts/graphs, gauges and maps are incorporated in the summary view and the multi-dimensional view of a dashboard application - as they help accommodate a large amount of data on a limited screen space.

Use of data visualization elements not only helps in optimizing the use of screen real estate, it also aids in quick comprehension of data.  Dashboard users are quickly able to identify the high and low values in the data and they also acquire an idea of the trend with which the data is changing.

Data Visualization Elements

As stated above, data visualization elements that are incorporated into a dashboard can be classified into three categories:

  • Charts/Graphs
  • Gauges
  • Maps


Charts help in the visual representation of tabulated numeric data.  Data in a chart is represented by means of symbols, such as bars in a bar chart, lines in a line chart and slices in a pie chart. The purpose of putting charts on a dashboard is to assist the user in analyzing the data.  Most dashboard users are interested in following these types of analyses:

  • Comparison
  • Composition
  • Comparison of composite data
  • Trend
  • Trend versus comparison
  • Elimination / progressive reduction

Each type of data analysis requires the use of specific chart types.  For instance, comparison of  data can be done using column or bar charts.  It is essential to understand each type of data analysis, so that an appropriate choice of charts can be made.

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