The Challenges of Gaining Useful Insight into Data
While there is a lot of interest in the potential of machine learning software, tapping into those capabilities is a major undertaking.
Looking to make machine learning software more accessible, Adatao today released the Adatao Data Intelligence Platform, a comprehensive stack of software that includes everything from a predictive analytics engine to the dashboards needed to query data stored in the platform.
While Adatao is aiming to deliver a comprehensive machine learning platform, Adatao CEO Christopher Nguyen says the company has also made sure that there are open application programming interfaces (APIs) at every level of the stack. That way, organizations that have already invested in other analytics applications can just as readily invoke any component of the Adatao platform as any other module in the stack.
Nguyen says the primary issue with machine learning technologies at this point is not the core technology, but rather making the data from these applications more broadly accessible. Nguyen says we’re moving toward a world where software is intelligent enough to detect patterns and identify anomalies. The challenge will be finding the best ways to make that information available to end users in a way that provides actionable intelligence, says Nguyen.
In the case of Adatao, Nguyen says that means integrating with everything from the open source R programming language to Microsoft Office.
While it’s still relatively early in terms of mainstream machine learning software adoption, the fact that IT organizations can now store massive amounts of data relatively inexpensively provides foundational component for artificial intelligence (AI) applications that has been long missing. Combine that with massive amounts of compute horsepower in the cloud and the stage in the years ahead is set for a massive leap forward in the sophistication of enterprise application software.
