Exclusive Interview: Chris Westphal, Visual Analytics
November 12, 2012
With the hype surrounding analytics, I have difficulty separating the wheat from the Wheaties when it comes to companies offering next-generation . Since the election, some individuals have been positioned as superstars of analytics. (The full text of my interview with Mr. Westphal appears in the ArnoldIT Search Wizards Speak series at this link.)
I am not comfortable with political predictions nor the notion of superstars. I did some checking and got solid referrals to Chris Westphal, one of the founders of Visual Analytics. The company has a solid client base in the world where analytics are essential to security and risk mitigation.
Mr. Westphal was gracious with his time, and I was able to speak with him in Washington, DC and then continue our discussion via email. In the course of my conversations with Mr. Westphal, he provided a different perspective on the fast-growing analytics sector.
His company, Visual Analytics or VAI is a privately-held company based in the Washington, DC metropolitan area providing proactive analytical, decision support, and information sharing solutions in commercial and government marketplaces throughout the world for investigating money laundering, financial crimes, narcotics, terrorism, border security, embezzlement, and fraud.
He told me that his firm’s approach and its success are a result of focusing on client problems, not imposing a textbook solution on a situation. He said:
We are problem driven. One of the most important areas we have found that separates us from much of our competition is the ability to deliver actual “analytics” to our end-user clients. It is not simply running a query looking for a specific value or graphically showing the contents of a spreadsheet. Our approach is to exploit the patterns and behaviors that are hidden with in the structures and volumes of the data we are processing. Our system effectively taps multiple, disparate sources to deliver one of the industry’s only federated data access platforms. We continue to focus on how to create algorithms (in a generic fashion), that can detect temporal sequences repeating activities, commonality, high-velocity connections, pathways, and complex aggregations.
One of the keys to Visual Analytics success is the company’s distinction between analytics and monitoring. Mr. Westphal pointed out:
The world is full of very good data management systems. There are databases, crawlers, indexers, etc. Our approach is to provide a layer on top of these existing sources and provide “interface-compliant-queries” to pull out relevant content. In about 90 percent of our engagements, we take advantage of the existing infrastructure with little to no impact on the client’s information technology processes, networks, or hardware footprint. If special processing is required, we tune the data management application to best meet the structure of the data so it can be processed/queried to maximize the analytical results. One other discussion is to differentiate “analytics” from “monitoring.” Much of our capability is to expose new patterns and trends, define the parameters, and verify data structures, content, and other key factors. Once we’ve locked in on a valuable pattern, we can continue to look for the pattern or it can be recoded into another system/approach (e.g., like is typically done with inline transactional systems) for real-time detection. The hard-issue is detecting the pattern in the first place.
The technical approach of Visual Analytics relies on open source and proprietary systems and methods. Mr. Westphal noted:
We have a very robust data connection framework consisting of different methods for different purposes. The core “connectors” are for relational databases and are based on standard database connector protocols. Our system also has drivers to other platforms such as information retrieval systems, various enterprise systems, plus the ability to create custom web services to expand, where necessary, to handle new sources or systems (including proprietary formats – assuming there is a Web-service interface available. We also have Apache Lucene built into our application at the data-layer so it can crawl and index content as needed. We try to make options available along with guidance about each approach. We offer a collection of methods to deliver the right-content for meeting a wide range of client needs. We always reference “contextual analytics” which basically means providing the actual content or pointers to content for any data entity – regardless of where it resides.
The full text of the interview is available at http://goo.gl/2y6T8. After my discussions with Mr. Westphal I remain convinced that the notion of next generation analytics is more rich and mature than some applications of next generation analytics.
Stephen E Arnold, November 12, 2012
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