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What is a Dashboard?

ITech Analytic Solutions
30/12/2016 0 0

Introduction

There are many different ideas of what a dashboard is. This article will clearly define it along with other presentation tools. In article, What is BI? - A Business Intelligence Primer, it is discussed the presentation layer of the business intelligence technology stack. To reiterate, there are typically four types of presentation media: dashboards, visual analysis tools, scorecards, and reports. These are all visual representations of data that help people identify correlations, trends, outliers (anomalies), patterns, and business conditions. However, they all have their own unique attributes.

Dashboards

Dashboard Insight uses Stephen Few’s definition of a dashboard:

A dashboard is a visual display of the most important information needed to achieve one or more objectives; consolidated and arranged on a single screen so the information can be monitored at a glance.

Here are the key characteristics of a dashboard:

  • All the visualizations fit on a single computer screen — scrolling to see more violates the definition of a dashboard.
  • It shows the most important performance indicators / performance measures to be monitored.
  • Interactivity such as filtering and drill-down can be used in a dashboard; however, those types of actions should not be required to see which performance indicators are under performing.
  • It is not designed exclusively for executives but rather should be used by the general workforce as effective dashboards are easy to understand and use.
  • The displayed data automatically updated without any assistance from the user. The frequency of the update will vary by organization and by purpose. The most effective dashboards have data updated at least on a daily basis.



Visual Analysis Tools

Some consider tools that offer the ability to select various date ranges, pick different products, or drill down to more detailed data to be dashboards. At Dashboard Insight, we classify these as visual analysis tools.
Here are the key characteristics of a visual analysis tool:

  • It fits on one screen, but there may be scroll bars for tables with too many rows or charts with too many data points.
  • It is highly interactive and usually provides functionality like filtering and drill downs.
  • It is primarily used to find correlations, trends, outliers (anomalies), patterns, and business conditions in data.
  • The data used in a visual analysis tool is generally historical data. However, there are some cases where real-time data is analyzed.
  • It helps to identify performance indicators for use in dashboards.
  • It is typically relied on by technically savvy users like data analysts and researchers.



Scorecards

Scorecards and dashboards are often used interchangeably, but Dashboard Insight has a specific definition:

A scorecard is a tabular visualization of measures and their respective targets with visual indicators to see how each measure is performing against their targets at a glance

In addition, it should not be confused with Kaplan and Norton’s Balanced Scorecard. Here are the key characteristics of a scorecard:

  • It contains at least a measure, its value, its target, and a visual indication of the status (e.g. a circular traffic light that is green for good, yellow for warning, and red for bad) on each row.
  • It can be used in a dashboard but the scorecard should not be interactive nor contain scroll bars.
  • It can be used in a visual analysis tool but the scorecard doesn’t need to be interactive.
  • It may contain columns that show trends in sparklines.



Reports

Reports contain detailed data in a tabular format and typically display numbers and text only, but they can use visualizations to highlight key data.
Here are the key characteristics of a report

  • It presents numbers and text in a table.
  • It can contain visualizations but only used to highlight findings in the data.
  • It is optimized for printing and exporting to a digital document format such as Word or PDF.
  • It is geared towards people who prefer to read data, for example,  lawyers, who would rather read text over interpreting visualizations, and accountants, who are comfortable working with raw numbers.
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