Quite quickly TLViz proved it was an excellent tool for all sorts of trend data, not just OpenVMS system performance trends. I have personally used it for example with environmental data gleaned from World Watch and with employment data from the Bureau of Labor Statistics (BLS) once these data streams were converted to readily reusable format. Once we had made this data transformation, we realized that TLViz made it possible to discover previously invisible patterns that would have been more difficult to find if we had limited ourselves to the World Watch or the BLS tools that came with the original data.
TLViz is not the end all or be all for graphical trend analysis. It has undergone a series of enhancements and improvements over the past 6 years and yet in some ways it is really only at the beginning of what else might be accomplished.
The virtue of TLViz is that like MS Excel it is a generic tool. It works with any trend data, not just stock prices. Once you add a feature, it can then be available for everyone. And, you may be surprised to find that TLViz provides capabilities today that are radically more time efficient than even the best stock market tools for certain heavily used types of graphic representation. One example is the ease of combining metrics on a single chart. We will be delving into these advantages with specific examples in future posts.
Third: by using readily reusable data as its base, TLViz helps further promote the idea of ready reusability (R-R). What this means is that someone else can come along and build another generic utility that does something else magical and wonderful with trend data and that once that happens, these new capabilities will be available to everyone who has created or converted their data to the R-R form. For example, there is now a utility called CSVPNG (more about this in future posts) that takes R-R data and provides an additional set of capabilities that extend beyond what TLViz can do. And of course, if you use R-R data, you will still be able to use Excel, or Oracle, or MySQL on these data sets.
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