Since that article additional value has been exponentially created. Using their higher stock price they smartly allocated the capital they created to make a critical BI industry game changing synergistic acquisition for Panopticon, a Swedish software developer of data visualization tools.
Now with the future integrated products their software solutions will allow them to compete directly with Tableau (DATA) , Splunk (SPLK) and many other BI related vendors.
I was lucky to stumble upon this article published 09/30/13 in Datanami, Datawatch's Big Visualization Strategyfor Data. by Alex Woodie
The article was so well written I'm going to take parts and paste below in italics and quotes.
Datawatch was interested in doing what “vendors like Tableau Software and QlikTech were doing with data visualization”.
"We started evaluating companies we felt could add the capability to visualize the vast majority of data we were looking for," says Ben Plummer, a BI industry veteran who joined Datawatch recently as its chief marketing officer and senior vice president of strategic alliances. "We looked at eight to 10 companies, to be honest. Michael and I had both looked at Panopticon in the past. I looked at it when I was an IBM, and he looked at it while he was at Applix."
“Datawatch has already completed the first phase of integrating the Windows-based desktop interfaces for the two products. Full integration of the desktops and server components will take one to two years.”The eventual goal is to deliver a single product that combines Datawatch's capability to ingest and understand less-structured data sources with Panopticon's data visualization and exploration capability, and to bring the resulting technology to bear against both historical and real-time stream data. Few vendors, if any, can offer this capability today, Plummer says.
"The vision of Datawatch 2.0 is to deliver a soup-to-nuts product that gives customers the capability to analyze all of their data assets. "We want to give customers the capability to combine traditional structured data, unstructured data, and real time data to deliver both historical perspective and operational intelligence simultaneously," Plummer says. "Right now, there's no other technology in the industry doing this."
In the near future, Datawatch will announce a new in-memory database technology for the Panopticon piece, Plummer says. This will give customers the capability to visualize larger data sets than they currently can, he says. This will be useful for exploring historical data, but it won't be of much use for the real-time component, where data is in and out of the Datawatch software very quickly.
For now, the focus is on competing with the likes of Tableau, and maximizing the present, or what Plummer calls "real real time."
"We're literally able to take streaming data directly from its origin--whether it's coming from a trading system or machine sensor or a message bus--ingest it and visualize that immediately," he says. "The other vendors out there ingest it, put it in a database, and then visualize it. We're real real time, which makes us different. And we can do the historical stuff too. And then the question is, do we want to go and predict the future with that? It's always a possibility." Source Datanami by Alex Woodie
The bottom line , I see them immediately being able to make a serious run against Tableau (DATA) and Splunk (SPLK).
Tableau (DATA) is a nice piece of software but is more of a one trick pony, in my opinion. I’m sure they will try to address that issue in the future. Tableau is good software for graphs. It pivots data similar to Excel’s Pivot table functionality. The data must be in a structured table format to ingest. The data is then identified as either a dimension (text data) or measures (numerical data). Then you have options to drag the dimensions to columns or rows. After that you select what measures/numerical data you want to see as it relates your selected dimensions in the columns or rows combination. You can also filter the data just like an Excel pivot table. Finally there is a show me option that allows you to select what kind of view is best for the data. You can select bar chart, pie chart, circle plot, scatter plot, table, heat maps, tree map, gannt chart, bubbles or maps. It’s a nice function.
I see Datawatch as having a tremendous advantage over Tableau for some the following reasons but not nearly all. Datawatch software lets you access any structured, semi structured or unstructured data sources. You can combine that data with existing relied upon reports or data researched on the internet by saving as txt,xps or html.You can also quickly join on the fly to internal Access queries or Excel models. You get the idea and potential with unlimited data flexibility and access. Now add that to a world class real time visual data discover with Panopticon.
Splunk (splk) analyzes machine data. Machine data means they look at log files, that's all. Then they can search for key words or phrases. That data is then graphed. Datawatch has been analyzing log files for about 20 years. Datawatch has not put any direct effort to sell into that space. But now with Panopticon game on. One of many advantages with the Datawatch solution is they don’t just search for keywords like Splunk but instead parse the data into usable relatable data that can be further enhanced from other sources. Yes Panopitcon visual discovery is more advanced than Splunk. It would not surprise me if Splunk embedded panopticon into their software for better visualizations. Many well known software vendors have purchased the rights to use Panopticon advance visual capabilities.
Sorry Splunk but Panopticon has been detecting fraud, anomalies or just identifying opportunities within the uber high risk world of wall street's best risk management shops. They have also helped identify opportunities to increase profits, reduce operational and investment risks with their visual data monitoring and analysis tools in real time.This all before Splunk was a company.
I’m excited for Datawatch’s future as a long term customer that expects additional useful analytical functionality and a long term investor.