Data Visualization Practice

Charts, maps, color-coded tables, and other visual presentations are among the best ways to make sense out of large, complicated sets of data.  Some people consider these representations "frills" and insist on "plain facts." However, we believe that well-designed visuals expose relationships in datasets that are nearly impossible to recognize without them. Rich multidimensional charts and maps help to communicate information efficiently and clearly.  Properly constructed, they are invaluable time saving tools and, not to mention, aesthetically pleasing.

Data visualization is both dependant upon and closely related to data mining.  Before information can be represented visually, it has to be produced via analysis.  For more information on this subject please follow this link to our data mining practice area.

At Friedrich Klatt and Associates, we are conversant with the literature in this area, including classics such as Edward Tufte's series on displaying information: The Visual Display of Quantitative Information, Envisioning Information, and Visual Explanations.

Charts

In addition to the standard data-driven line, bar, and pie charts that we are all familiar with, we have created rich, multidimensional charts such as panels of pies, three-dimensional bubble charts, pies overlaid on maps, and many others.  Not only do we use popular charting tools such as SPSS, Crystal Reports, Access, and many others, but we have also developed our own charting application, the Visual Chart Production System.  We designed Visual Chart from the ground up using an architecture that allows us to embed the program seamlessly into larger applications.

Visual Chart provides rich WYSIWYG facilities to design charts. It stores templates for creating charts in user-defined folders, and organizes the folders in an outline much like the one found in Windows Explorer.  The application can merge data into any set of these templates and either print the resulting charts or generate Adobe Acrobat files. Visual Chart can do this either interactively or in an unattended batch production environment. It can be loosely coupled to data sources via simple ASCII text files, or more tightly coupled to direct data sources of host applications.

Maps

Color-coded maps are another great way to visualize data. For details, see our Geographic Analysis Practice.