Anomaly detection company Prelert is making a positive play for developers this month with its Anomaly Detective analytics engine, which will now enjoy an open API.
Enterprise developers can now "harness the power" of machine learning based anomaly detection analytics to manage complex online services, detect the earliest signs of advanced security threats, and gain insight to business opportunities and risks represented by changing behaviors hidden in their massive datasets.
"The massive datasets generated by the rapidly expanding world of the Internet of Things are so large and complex that it's virtually impossible for humans to spot important behavioral changes that could solve key issues, reveal the next big ideas, or even open doors to whole new markets," said Jeffrey M. Kaplan, Managing Director of IT strategic consulting firm, THINKstrategies. "The only way to overcome this challenge and capitalize on this unprecedented opportunity is to leverage machine-driven analytics that flag anomalous behaviors of significance so organizations can act on them."
Prelert's Anomaly Detective uses advanced analytics based on "unsupervised machine learning" to process huge volumes of streaming data, automatically learn normal behavior patterns represented by the data and identify and cross-correlate anomalies.
Prelert's analytics engine routinely processes millions of data points in real-time and identifies performance, security, and operational anomalies and their causes as they develop so they can be acted on before they impact business.
"Explosive growth in computing scale and the accompanying data it generates have made it increasingly difficult for software developers and DevOps practitioners to discover problems that arise in these massive infrastructures," said Donnie Berkholz, analyst at the developer-focused firm RedMonk. "By providing an open API to its anomaly detection engine, Prelert is addressing this need by enabling developers to leverage its machine learning tooling in their projects — whether the data is stored in a proprietary database, Hadoop, or another SQL or NoSQL data store."
Prelert's API provides a REST interface that allows real-time or batch analysis of massive datasets by its anomaly detection engine. A free license of Prelert's anomaly detection engine and API is available for download at info.prelert.com for evaluation, development, and testing.
