Why clario? Technologies Converge

I have the pleasure to introduce a new guest blogger on Data Mining Research: Matt Redlon. He is the Chief Technology Officer and Co-Founder of Decision Intelligence. His post is about clario, a new business analytics platform.

clario was born of many motivations. As the industry’s first Web-hosted analytical platform for database marketers, I’d like to address what is perhaps the most significant motivation: an observation that three converging trends present a stunning opportunity for a new predictive analytics platform.

“Web 2.0”
Yes, I’m aware the phrase is ubiquitous to the point absurdity. But, let’s constrain the definition to two frequent features of this umbrella term: rich Internet applications (RIA) and collaboration. With rich, desktop-like user interfaces now possible via the Web browser, a major hurdle to deploying applications requiring complex user interactions and visualizations has been overcome. Additionally, unlike traditionally deployed applications, the collaborative capabilities of a Web-deployed application allow both producers and consumers of an organization’s predictive analytics to break free of their traditionally cloistered existence, significantly enhancing productivity.

READ

Big Data, Data Mining and Machine Learning: Deriving Value for Business

Software-as-a-service (SaaS)
The tremendous growth of SaaS over the last two years is a testament to the real value the model offers to both providers and users. As much a business model as a technology, SaaS shifts the technology burden from the user to the vendor, lowering upfront costs and time to productivity, and ensures fast turnaround of new functionality. A key benefit to users of SaaS applications is the ability to subscribe for one low monthly price, paying for what you use, when you use it, versus large up-front license fees.

Third, cloud computing.
Blogger and author Nicholas Carr recently summed up the dramatic transformation occurring in computing in his book The Big Switch: Rewiring the World, from Edison to Google. The fantastic implications of the transition to utility enterprise computing he describes are particularly well suited to a data mining application. The critical observation is that enterprise analytics require significant computational resources for relatively short periods of time (or “bursts”). Purchasing and maintaining the resources to support these analytic bursts is economically prohibitive for many organizations. clario’s unique cloud architecture presents an organization with the unique opportunity to purchase access to massive computing resources, paying only for the bursts of analytic horsepower they require.