The Defense Advanced Research Projects Agency, also known as DARPA, recently awarded $3M to data visualization and analytics company Continuum Analytics. They have earmarked the funds to develop data analytics and data processing libraries for Python, a popular computer programming language. DARPA is spending $100M over four years to advance Big Data technologies. Wikibon Analyst Jeff Kelly weighed in on the Big Data announcement.
When asked what the federal government’s interest is in a project to make writing Big Data applications easier, he stated, “The federal government is one of the early adopters of Big Data technology . . . the Defense Departments, as well as the CIA and others, are users of Big Data technologies for things like counter-terrorism operations.” He elaborated on how this applies to both the intelligence and non-intelligence side of Big Data.
Continuum Analytics plans to develop two specific projects with the funding. Blaze will be a scientific computing library for the Python computing language. According to Kelly, it will take existing Python libraries and make them easier to apply to Big Data use cases. The second project, Bokeh, deals with applying scaleable, attractive data visualizations to large data sets using Python.
“Python was not designed as an application language . . . with large data sets in mind, so these are projects to help Python be applied to Big Data,” Kelly explained.
He cited numerous reasons why big data application development is so important. He also highlighted that the value of Big Data is found in applications that automate processes where government agencies can react quickly, as well as applications that business users interact with to visualize business data. However, Big Data still faces big challenges in that there are very few tools available to design these Big Data applications.
Kelly noted that we’re starting to see movement in the Big Data application development space. He referenced Continuity, a company which is building out a data fabric layer that allows developers to easily interact with large data sets to build Big Data applications. See the entire segment with Kristin Feledy and Jeff Kelly on the Morning NewsDesk Show.