InfoQ Homepage Database Content on InfoQ
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Developing a Machine Learning Based Predictive Analytics Engine for Big Data Analytics
Ali Jalali presents how to develop a machine learning predictive analytics engine for big data analytics.
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How to Train Your Microservice
Doug Sherman reviews the efforts that took place in the initial phases which incorporated targeted parts of the Spring Framework, as well as more current efforts that leveraged Spring projects.
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MongoDB-as-a-Service on Pivotal Cloud Foundry
Mallika Iyer and Sam Weaver cover a brief overview of Pivotal Cloud Foundry and deep dive into running MongoDB as a managed service on this platform.
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Wall St. Derivative Risk Solutions Using Geode
Andre Langevin and Mike Stolz discuss how Geode forms the core of many Wall Street derivative risk solutions which provide cross-product risk management at speeds suitable for automated hedging.
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What They Don't Tell You about Microservices...
Daniel Rolnick talks about the process Yodle went through adopting and deploying microservices, including database architectures and architectural patterns that emerged.
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Persistence Arrives on Cloud Foundry
Paul Warren explains how the CF runtime was extended to include persistent storage, demonstrating scaling an application that accesses data on a NFS volume and discussing the future of persistence.
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The Joy of Analysis Development
Hilary Parker discusses the history of the analysis development tools, the current state of the art, and the importance for data scientists and analysts to understand programming principles.
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Using Clojure and Neo4j to Build a Meetup Recommendation Engine
Mark Needham shows how a meetup recommendation engine using Neo4j and Clojure can be built from scratch, combining content-based and collaborative filtering using Cypher and Clojure.
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Exploring Wikipedia with Apache Spark: A Live Coding Demo
Sameer Farooqui demos connecting to the live stream of Wikipedia edits, building a dashboard showing what’s happening with Wikipedia datasets and how people are using them in real time.
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Adaptive Availability for Quality of Service
Theo Schlossnagle talks about lessons learned in building an always-on distributed time-series database with aggressive quality of service guarantees, and techniques for dealing with bad machines.
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Ingest & Stream Processing - What Will You Choose?
Pat Patterson and Ted Malaska talk about current and emerging data processing technologies, and the various ways of achieving "at least once" and "exactly once" timely data processing.
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Structuring Data for Self-Serve Customer Insights
Jim Porzak discusses creating an analyst ready data mart that is complete at different levels of abstraction and models customer decision points in order to be able to understand customers.
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