Earlier this week, we announced the release of Spotfire 2.2, the latest update to the Spotfire platform.  It's always good to get an update to the platform into the market, and we've made some great strides with Spotfire this year (a topic for another post), but I'm particularly pleased with some of the things we've added in this release.

Spotfire has historically (10+ years) been a leader in in-memory, interactive visualization, and given how much end users like being able to actually understand their data, it's not surprising that we've started to see other vendors adding some data visualization capabilities to their offerings.  Not-unrelatedly, we've started to get some questions about whether or not our core historical strengths were enough to continue differentiating ourselves from the rest of the market.

Without getting into the other things that we're doing to marry user-driven analytics with predictive analytics, event-processing and other enterprise technologies, the 2.2 release of the Spotfire platform provides a great response to questions about how Spotfire is different.

The two biggest additions are both new visual analysis tools:

The 3-D Plot allows for the visualization of multiple dimensions on a single plot.  While you can add multiple dimensions to a 2-D dot plot with the use of color, shape or size, or by trellising multiple plots, it's not always easy to identify trends within groups, or across different plots.

The 3-D plot addresses some of those challenges, and provides an understandable visual framework for displaying results from statistical techniques such as Principle Components Analysis (a dimension reduction technique for highly multi-variate data).

It's also great for cases, such as the example shown here--measurements from the drill hole of an oil well--where the actual data are measurements made in three dimensions.

Network Analytics, a extensible visualization tool for navigating and analyzing networks, is built entirely using the Spotfire public SDK, and it's something that I'm really excited about.

Wearing my analysis-loving geek hat, I think that analysis of networks is going to be one of, if not the, hottest area of data analysis in the not-too-distant future.  It's been used extensively for years in a few areas such as intelligence and other specialized fields, but its value is becoming more and more evident as everything becomes ever-more connected.

For instance, I'm a member of a Harvard-sponsored working group on Food Safety (last meeting detailed here), and it's absolutely critical for the FDA to be able to quickly traverse the immense network of food suppliers when there is an outbreak of food-borne illness, not only to identify the source, but to quickly clear the suppliers whose products aren't at risk.

That's not something that can be readily done with other types of visualization or analysis techniques.

Similarly, social networking sites such as LinkedIn, Facebook, Twitter and others create networks, the analysis of which is interesting to many, and a real business opportunity for folks who would like to advertise to targeted groups of consumers.  Such networks are only going to proliferate in the future, and the ability to understand them will be key to decision making across industries and disciplines.

Beyond those two items, there are a number of other improvements to the platform, but it's these two pieces that I'm really excited by.