This new core security layer provides a unified data access path for all Hadoop ecosystem components, while improving performance.
We’re thrilled to announce the beta availability of RecordService, a distributed, scalable, data access service for unified access control and enforcement in Apache Hadoop. RecordService is Apache Licensed open source that we intend to transition to the Apache Software Foundation. In this post, we’ll explain the motivation, system architecture,
The super-active Apache Spark community is exerting a strong gravitational pull within the Apache Hadoop ecosystem. I recently had that opportunity to ask Cloudera’s Apache Spark committers (Sean Owen, Imran Rashid [PMC], Sandy Ryza, and Marcelo Vanzin) for their perspectives about how the Spark community has worked and is working together, and the work to be done via the One Platform initiative to make the Spark stack enterprise-ready.
Thanks to Barclays employees Sam Savage, VP Data Science, and Harry Powell, Head of Advanced Analytics, for the guest post below about the Barclays use case for Apache Spark and its Scala API.
At Barclays, our team recently built an application called Insights Engine to execute an arbitrary number N of near-arbitrary SQL-like queries and execute them in a way that can scale with increasing N.
To design effective fraud-detection architecture, look no further than the human brain (with some help from Spark Streaming and Apache Kafka).
At its core, fraud detection is about detection whether people are behaving “as they should,” otherwise known as catching anomalies in a stream of events. This goal is reflected in diverse applications such as detecting credit-card fraud, flagging patients who are doctor shopping to obtain a supply of prescription drugs,
Our thanks to Karthik Vadla and Abhi Basu, Big Data Solutions engineers at Intel, for permission to re-publish the following (which was originally available here).
Data science is not a new discipline. However, with the growth of big data and adoption of big data technologies, the request for better quality data has grown exponentially. Today data science is applied to every facet of life—product validation through fault prediction,