This paper has described the seven defining elements of visual analytics applications. Yet there are other factors to consider before making a choice on a visual analytics standard. For instance, if the visual analytics application is going to be used in a corporate environment, there are technical and infrastructure considerations as well.
Universal Data Access. Data comes from all directions. Does the software connect to virtually any source, from data warehouses to Excel or text files? Does it connect to all major data formats, including relational databases, OLAP data cubes and flat files? Furthermore, is connecting to new data sources easily done?
Scalability. Does the software support real-time interactive visualization of data of nearly any size—even millions or billions of records? The application should be able to handle large amounts of data and provide solid performance.
Generates Efficient SQL for DBMS. Reports should generate quickly. People should have the option to take, modify and run SQL from the reports and reproduce the results. They should also be able connect to SQL statements rather than actual data tables and views.
Ability to Join Tables. People should be able to join tables easily in ways that guide them to appropriate and well-designed joins. Tables can be joined automatically or based on user’s direction.
Security. Does the application have a full security module to support collaboration within existing permission systems? This should include optional integration with other security methods like Active Directory.
Minimal IT Support. Good software frees IT from the small stuff. Good software installs easily, gets the average user up in minutes without help, and provides free training on demand.
Microsoft Office Compatibility. MS Office is ubiquitous on the business person’s desktop. Does the software provide gateways in and out of MS Office? Can users natively access data from Office applications? Can they output images, tables, data lists, cross-tabs easily and directly to Office?
Data Modeling and Management. Can users share entire data models used to construct visualizations— along with individual calculations, groups, etc? Users should be able to rely on dimensions and measures that are consistently defined and have data integrity. Can the software allow the user to model data –- such as to modify variable types, replicate variables, change field names, standardize dimensions -- without developer support? This is critical for giving users the analytical power while also reducing the IT burden.
Training. How much is needed? Ideally people can get started without any training – the user interface should be obvious and easy to use. Is there free online training available any time for multiple levels? As people advance in their visual analytic skills, more sophisticated training should be available on their time schedule based on their needs.
Licensing. Licensing models should be flexible based on user needs without minimum configurations: buy 1 license, buy 10, buy 100, buy 1000.