10 Different Business Intelligence Visualization Models

Visualization is the critical output of quality business intelligence. The process draws on vast and disparate data sets that exist only as baffling collections of numbers, facts, and figures. Modern visualization tools go beyond just whipping these disparate datasets into charts, however; they apply advanced AI, sophisticated machine learning, and complex algorithms to give the data form and function.

What results are visual representations of that data? The advantage of this over something like a spreadsheet or a more clinical form of report is that it literally illustrates the insights contained within the data. Decision makers can see clearly how objects of comparison interact and track.

Visualization is not an end, in and of itself, but rather a toolkit that decision makers use to enhance the planning process. As such, there are many different visualization models, each useful for different reasons. Here are 10 worth experimenting with:

 

  1. Line Chart – This is one of the oldest types of visualizations, and it remains popular because it applies to a number of different business intelligence scenarios. It is particularly good at expressing trends forecasted out over time, or for comparing disparate groups of data over the same time period.

 

  1. Indicator – If you need to express a change in the simplest terms an indicator is ideal. It is simply a way to tag a specific figure with an indicator of its previous position. For instance, an up arrow would indicate that a figure was rising, or text printed in red could demonstrate a falling position.

 

  1. Column Chart – Similar to the line chart, this visualization is popular for expressing trends and presents information in an immediately digestible format. A combination of a column chart and a line chart is especially useful for comparing present and historical data over the same time periods.

 

  1. Bar Chart – The bar chart is deceptively useful for business intelligence because while it seems simple it incorporates a lot of different data into one comprehensible chart. For that fact alone it is particularly useful for spotting anomalies.

 

  1. Pivot Table – Think of this as a snapshot of a spreadsheet that has been organized to be quickly comprehensible. The advantage of a pivot table is that it summarizes large amounts of data succinctly and gives the analyst a lot of freedom over how they compare and format the results.

 

  1. 3D Graphic – Advanced BI visualization tools allow for multiple types of 3D modeling. Since this technology is still relatively new, applications and business cases are still being worked out. But having a new dimension to express informational relationships with opens up significant new opportunities for business intelligence.

 

  1. Area Chart – The style of this visualization is similar to a line chart. But since the area beneath each line is filled in it adds another point of comparison between data sources. This format is particularly useful when looking at data arranged along a timeline.

 

  1. Pie Chart – This remains the best type of visualization for displaying proportions or percentages. The key to using pie charts successfully is to ensure that the sum of the parts is meaningful from an intelligence standpoint and that there are not too many pieces portioned into the pie.

 

  1. Scatter Chart – If you want to explore the relationship between several variables with a BI visualization tool in a nuanced way, the scatter chart is highly illustrative. Relationships between variables that would otherwise not have been apparent jump out in this format.

 

  1. Treemap – When other types of visualization become cluttered with information the treemap becomes useful. The combination of color coding, special relationships, and a hierarchical arrangement of information makes it easy to spot the relevant insights in large data sets.

Making the most of visualizations for the purposes of business intelligence is all about being flexible. Decision makers should rely on a wide range of visualizations, identify the ones they find most useful, and be open to the alternate perspectives offered by different formats. Relying on a solid BI visualization tool makes it easy to re-contextualize data quickly and comprehensively.

 

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