Thoughts on the Gartner Magic Quadrant: What to Do When Issues Persist Across BI Platforms
Intro
Every year, Gartner publishes Magic Quadrants to identify and compare competing players in different tech markets across two different scales: Completeness of Vision and Ability to Execute. Over the last couple of years, Gartner’s Magic Quadrant for Analytics and Business Intelligence has sparked some lively discussions in our Data Visualization practice, especially regarding the rankings of Tableau and Microsoft (Power BI), the two highest-rated platforms on the report. This year, after we moved past our personal preferences, we started talking about common issues that we have run into at different client offices. No matter what platform is being used, we have heard from teams who are facing the following issues:
That leads us to ask “Why?”. Why do we consistently see these issues, even on the platforms that are leaders in this space?
The Cause of Many BI Problems
The companies profiled in the Magic Quadrant have developed powerful, accessible analytics platforms that allow users to quickly turn raw data into insights and share their findings with others. Sometimes, this sharing happens too quickly. There are times when new users get their hands on these tools without having proper knowledge of either the platform itself, the data they’re using, or both, and, before they know it, they have built dashboards to share with their team. These dashboards can end up in production before they are thoroughly vetted and stress-tested. Business users might see these premature dashboards and start questioning the results and wondering why the dashboards take so long to load. This can lead to the development of additional dashboards and reports to address these new issues, and the process starts all over again. If this happens frequently enough, servers can get bloated and difficult to manage very quickly.
How to Mitigate Against (or Prevent) These Problems
So how can you mitigate these issues or prevent them in the first place? Our team recommends designating separate time devoted to Data Discovery and Dashboard Development. The scenario described in the last section is what happens when these two phases are conflated; users connect to their data and start building right away before having a plan in place. Devoting the proper time and energy to Data Discovery and Dashboard Design can keep you out of that vicious cycle.
Data Discovery is crucial and should be the first phase of any data visualization project. It is when all requirement gathering, data exploration, and data definition happens. Knowing what data you need, where it is, and what the fields represent let you know if any additional data is needed or if your data needs to be manipulated for analysis. Data Discovery is like mapping out your route and getting your car serviced before a road trip; the up-front planning can save a lot of time and frustration on the way to your destination.
Dashboard Development is when dashboards and reports are created with your company’s BI platform using the data sources defined during Data Discovery. This is the phase when the dashboard or report is built. Decisions about dashboard design, functionality, and distribution are made during Dashboard Development. It is also when the dashboard is QA’d and stress-tested prior to deployment (to minimize the risk of having to de-bug your product). If Data Discovery is the preparation for your road trip, Dashboard Development is the driving itself. Barring any unforeseen issues, at the end of your trip you’ll have a brand-new production-ready dashboard.
Conclusion
Gartner’s Magic Quadrant can help you decide which modern BI platform to use at your company, but no platform is immune to process-related issues. Splitting projects into Data Discovery and Dashboard Development phases can ensure that all data and platform concerns are addressed prior to a dashboard going into production, leading to a smoother all-around experience.
If you have any questions about Data Discovery or Dashboard Development, please reach out to one of our Data Visualization specialists!
