Leading companies that are getting the most out of their data are not focusing on queries and data lakes; they are actively integrating analytics into their operations with a stream-first application development approach. Real-time adjustments to improve revenues, reduce costs, or mitigate risk rely on applications that minimize latency on a variety of data sources. Ted Dunning reviews best practices for three use cases in ad/media, financial services, and healthcare to show how customers develop, deploy, and dynamically update these applications and how this data-first approach is fundamentally different from traditional applications.
Along the way, Ted covers examples of how customers identified ways to simplify data streams in a publish-and-subscribe framework (for example, how focusing on a stream of electronic medical records simplified the deployment of real-time applications for hospitals, clinics, and insurance companies). Ted also details how a stream-first and data-first approach can lead to rapid deployment of additional real-time applications as well as centralize and simplify many data management and administration tasks.
This talk is sponsored by MapR Technologies.
Ted Dunning has been involved with a number of startups—the latest is MapR Technologies, where he is chief application architect working on advanced Hadoop-related technologies. Ted is also a PMC member for the Apache Zookeeper and Mahout projects and contributed to the Mahout clustering, classification, and matrix decomposition algorithms. He was the chief architect behind the MusicMatch (now Yahoo Music) and Veoh recommendation systems and built fraud-detection systems for ID Analytics. Opinionated about software and data-mining and passionate about open source, he is an active participant of Hadoop and related communities and loves helping projects get going with new technologies.
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