Complex business problems call for complex data analytics, and the complexities keep climbing. Analysts now bring back data from an ever-broadening collection of data sets, many of them massive. These disparate data must be painstakingly cleaned, extracted and integrated, and the results must be analyzed thoughtfully and presented understandably. Unsurprisingly, traditional tools such as spreadsheets often fail to pull all this together, and programming for customized analytics is often slow, expensive, and inflexible.
Composable Analytics, a startup firm that spun out of MIT Lincoln Laboratory, visualizes this problem differently—quite literally, since its business intelligence platform lets analysts visually design their own workflows for gathering and manipulating data from a series of sources.
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