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Comparing 3 popular business intelligence platforms

business-intelligence-visualIn the first post of this series, we evaluated three online tools for creating infographics. In that post, we noted that despite the abundance of tools available to researchers and business intelligence analysts, PowerPoint was still the most used for creating and presenting data visualizations. For years, researchers have been expected to ditch these types of over-simplified visualization tools (which aren’t particularly well suited for managing research data) in favor of other, more appropriate tools, like dashboards, interactive analysis, infographics, and web portals.

In order to help this transformation along, we're continuing our review of various data visualization platforms - this time, we've turned our attention to business intelligence platforms.

 

Business intelligence platforms


Among the integrated business intelligence environments, the tools that stand out for their data visualization and analysis features and capabilities are: Tableau, QlikSense, and Microsoft Power Bi. Although these providers lead the market in business intelligence, every business has to decide for itself which offering best suits its own needs. Let’s look at the pros and cons of each:

 

Tableau

QlikSense

Power Bi

Visualization capabilities
  • Attractive and intuitive visualization tool that makes it easy to create more complex graphics in real time, just by dragging the metrics.
  • Includes a powerful visualization suite that doesn’t require any prior programming knowledge. The results are of especially high quality, thanks to the fact that the data is processed as it is explored.
  • Integrates two levels of customization: through its native user interface, and through its use of open API/libraries.
  • Integration and extension: developers can build their own sophisticated dashboards.
  • Active community assisted by Qlik.
  • Simple, intuitive visualization tool.
  • Integrates a full, functional library of different kinds of graphics.

Advanced analytics capabilities
  • Integrated support for R and Python programming languages.
  • Native clustering and forecasting tools.
  • Predictive analytics, clustering, and regressions (only possible with API connections).
  • Supports R-based visualizations, including forecasting, clustering, and decision-tree analysis.

Data management
  • Excel spreadsheets, CSV, Google Sheets. Also provides embedded options for any web portal or webpage, as well as filters.
  • Allows data gathering from different sources, which makes it possible to explore the associations between different data points.
  • Excel spreadsheets, CSV.
  • However, cloud accounts are required to share visualizations.

Limitations
  • The paid version is expensive, and the free version has limitations, as it is public.
  • Imposes a subscription limit of 100 GB of storage for cloud data.
  • The paid version is quite expensive.
  • Fewer basic features than other software, such as Tableau.
  • May require additional payments.
  • Subscription limit of 10GB of storage for cloud data.

 

Of course, the tool that works best for you will depend heavily on your needs. Regardless, we hope this chart has given you some clarity and made it easier to find the most suitable tool. If you'd like to learn more about how to most effectively communicate your insights, you can now download our free guide on data visualization by clicking the link in the banner below.

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