Ryan Laspina, Associate Director, Admissions Data Analytics, Shenandoah University
Data AnalyticsData VisualizationInformation Technology

Customization is a Must for Data Visualization Software 

cxomagazine

By Ryan Laspina, Associate Director, Admissions Data Analytics, Shenandoah University

What makes a premier data analyst? Many traits can be considered. Still, one of the most important is an individual who blends the precise, calculating nature needed to ingest, transform, and report on data with the creativity to create visualizations that are easily digestible to stakeholders who frankly do not have the time to understand the depth of data analysis. Executive leaders want their data to be kept simple; visualization software is needed to accomplish this. 

All Tools are Not Created Equal 

There is a myriad of data visualization tools in the industry.  Some of these tools have the power to ingest all of your data and provide visualizations, such as PowerBI or Domo.  Others are used primarily for providing visualizations, such as Google Looker Studio.  Lastly, some are primarily used for data storage or as a CRM but offer some visualization capabilities, such as Hubspot.  The tool you need will depend on how much data you manage, as well as the complexity of the reporting needs. 

The most important rule to remember as a data analyst is that nearly everyone who receives your data analysis knows very little about data or the data transformation process.

Customization is the Key 

Data visualization tools do not have to have next-level processing power to be proficient.  There are plenty of benchmarks that a tool has to hit (how much data they can ingest, how granular they can drill down, etc.), but one of the musts to ensure those premier data analysts are reaching their full potential is extensive customization.  The ability to customize visualizations is what sets apart adequate visualizations from insightful visualizations.  Executives will judge the importance of a visualization in a split second – so it better be as impactful as possible.  The underlying data is going to be the same regardless of the tool that is being used; however, the effectiveness of that visualization completely depends on how customizable it is. 

Factors that Determine an Effective Visualization 

Here are some of the factors to consider when creating a visualization for stakeholders: 

  • Are there filters or buttons that need to be clicked to show the full picture?  If so, consider creating multiple visualizations so the information can be viewed in bite-sized chunks. 
  • What colors are being used?  Immediately using brand colors makes the visualizations more attractive and will hold the stakeholders’ attention for longer. 
  • If you are working on an entire dashboard, do your visualizations follow the KPI path?  High-level information should be at the top of the dashboard, while more granular KPIs should be lower down the page. 
  • Switch it up!  Looking at tables and tables of data is a surefire way to lose your audience.  Obviously, the type and flow of charts need to make sense, but stakeholders are much more apt to focus on pie charts, bar graphs, and overall diversity of visualizations.  Tables can be effective in some instances, but tables are essentially just a housing mechanism for raw data. 

Customizations to Look For 

If you are shopping around for a solid data visualization tool, the first area to explore is how customizable the visualizations are.  Here are some characteristics to look for: 

  • Graph types.  Bar charts and pie graphs are nice, but does the tool offer scatter plots?  Word clouds?  More advanced options provide you with more ways to report on data.  For example, a word cloud option is supremely helpful when it comes to survey responses. 
  • Customizable chart features.  Every aspect of your visualization should be customizable.  Want to change the colors of the lines in your line chart?  Want to be able to tilt your headings by 60 degrees?  Want to be able to show trendlines?  You want to find a tool that can mostly do anything you can dream of when it comes to creating visualizations.  The more customization, the less time you have to spend trying to figure out how to showcase inflection points in the data.  You want your visualizations to be aesthetically pleasing as well. 
  • Data ingestion.  There are always one-off scenarios where you may want to use an Excel lookup table in your visualization.  If your tool does not have customizable options for data ingestion, you might not be able to report on everything you want to.  There is a caveat to this, as uploading data without any structure or governance in place can be a slippery slope, but seasoned data analysts can handle a tool that provides multiple uploading options. 

Why Visualization Customization is Important 

The most important rule to remember as a data analyst is that nearly everyone who receives your data analysis knows very little about data or the data transformation process. Everything should be provided in context and in bite-sized chunks that will not overwhelm the audience. Extensive customization within your visualization tool is the best way to ensure that the stakeholders are actually digesting the analysis you are providing.  

There are plenty of factors to consider when looking for a data visualization tool.  While it is not the be-all and end-all, tools that allow for in-depth customization will profoundly impact your ability to present data in a way that decision-makers will appreciate.