Source: TechCrunch, Jan 2013
Ayasdi aims to automate the insight discovery process, allowing end users to find valuable intelligence within massive datasets almost instantaneously.
Research firm IDC recently predicted that the Big Data market is poised for exponential growth over the next few years, with total revenue projected to reach $24 billion by 2016.
The Ayasdi co-founders attribute this to the prevailing reliance among data scientists on old models — finding insights by asking questions and writing queries. The problem with this is that queries are inherently based on human assumptions and biases, and, in turn, query results tend to only reveal slices of data, rather than providing visibility into the relationships between similar groups of data. This method of discovering insight in Big Data tends to be rely heavily on iterative guesswork and chance, and thus takes time to produce real results.
To address this problem, Ayasdi is today officially launching its cloud-based insight discovery platform, which aims to deliver insight derived from massive datasets quickly, without relying on queries. The machine learning platform combines computer science with a branch of mathematics called “Topological Data Analysis,” which allows Ayasdi to visualize entire datasets at once.
The startup’s platform uses hundreds of machine learning algorithms to explore these complex datasets — the goal being the automatic discovery of insights that could not be discovered through ad hoc or query-based methods. The platform, which is designed for domain experts, data scientists and researchers, requires no coding or modeling and offers the kind of scalability that more demanding processing requires.