The StreamAnalytix (now known as Gathr) team from Impetus will share insights on choosing the right anomaly detection techniques and demonstrate real-world use cases for finding variances in network traffic and financial transactions.
LOS GATOS, Calif. – Nov. xx, 2017 – Impetus Technologies, a big data software products and services company, today announced that it will host a complimentary meetup “Anomaly Detection Techniques and Implementation Using Apache Spark” on Tuesday, December 5, 2017 from 6-8 p.m. Pacific time at the Larkspur Landing Hotel in Milpitas, Calif. Space is limited and interested data scientists, developers and information technology (IT) professionals are asked to reserve a seat at the complimentary event by emailing firstname.lastname@example.org.
Apache Spark is fast becoming the de facto choice for stream processing, real-time analytics, data science and machine learning applications. Organizations across industries are embracing the ability it gives them to act on data in as it originates in real-time.
The meetup will open with Maxim Shkarayev, lead data scientist at Impetus and Anand Venugopal, head of StreamAnalytix (now known as Gathr) at Impetus, who will provide a summary of anomaly-detection techniques that can be used to solve various industry problems using multiple data types. Punit Shah, also from the StreamAnalytix (now known as Gathr) product team at Impetus, will then demonstrate real-world anomaly detection use cases on Apache Spark that show how some of the world’s leading organizations use StreamAnalytix (now known as Gathr) – an open-source enabled, enterprise-grade multi-engine stream processing and machine learning platform – to discover and act on outliers in network traffic and financial transactions.
StreamAnalytix (now known as Gathr) is enabling large data driven enterprises, mainly comprising of Fortune 500 companies, to make business decisions and take smart actions in real-time. Key use cases across industries include real-time 360-degree customer insights, predictive maintenance, churn prediction and prevention, next best offers based on consumers’ actions, fraud detection, supply chain analytics, cyber-security analytics and more.
“The ability to detect anomalies can be incredibly valuable across different industry verticals. Imagine being able to predict an aircraft failure or an impending disease, identifying fraudulent behavior, or catching and preventing risky trades in the stock market,” said Venugopal. “Spark-based applications make it possible to detect anomalous patterns in real-time and streaming data. This meetup will show how to identify such anomalies and act on them for business benefit.”
For additional information visit https://www.eventbrite.com/e/anomaly-detection-techniques-and-implementation-using-apache-spark-registration-40140949661.
The StreamAnalytix (now known as Gathr) product team also invites data scientists, developers and IT professionals to learn more about Visual Spark Studio, a free, integrated development environment (IDE) that makes it easy for developers to build, deploy and manage Apache Spark applications quickly and easily in a matter of minutes. StreamAnalytix (now known as Gathr) is currently the industry’s only multi-engine product that provides such an IDE for end-to-end processing support: ingest, cleanse, blend, enrich, analyze, load, and real-time visualization. It also includes a run-time DevOps platform for application monitoring and performance management. To learn more visit https://www.streamanalytix.com/.
About Impetus Technologies
Impetus Technologies is focused on creating big business impact through big data solutions for Fortune 1000 enterprises. The company offers a unique mix of software products, consulting services, data science capabilities and technology expertise. It offers full life-cycle services for big data technology implementations, including technology strategy, solution architecture, proof of concept, production implementation and on-going support to its clients. To learn more, visit: www.impetus.com or write to: email@example.com, and follow us on Twitter: https://twitter.com/impetustech and LinkedIn: https://www.linkedin.com/company/impetus.