InfoQ Homepage Data Content on InfoQ
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Open Bank Project
Simon Redfern presents how the Open Bank Project innovates by leveraging open APIs, open source and open data, making banking data more accessible via an ecosystem of apps and services.
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Building a Distributed Data Ingestion System with RabbitMQ
Alvaro Videla shows how to build a system that can ingest data produced at separate locations and replicate it across regions using RabbitMQ.
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Data Modeling for Scale with Riak Data Types
Sponsored by Basho. Sean Cribbs discusses the theory behind several rich data types introduced with Riak 2.0 and then walking through some example applications that use them in popular languages.
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Building Connected Android Apps with Azure
Chris Risner demos an Android app built with Azure Mobile Services using structured data stored in the cloud, GCM push notifications with a single line of code, authentication, security and others.
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Finding the Needle in a Big Data Haystack
In this solutions track talk, sponsored by Cloudera, Eva Andreasson discusses how search and Hadoop can help with some of the industry's biggest challenges. She introduces the data hub concept.
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Data Movement at Very Large Scale
In this solutions track talk, sponsored by Solace Systems, Aaron Lee discusses the challenges moving information and techniques that can increase efficiency of data flows within big data architectures
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New Opportunities for Connected Data
In this solutions track talk, sponsored by Neo Technology, Ian Robinson takes a look at how size, structure and connectivity have converged to transform the data landscape.
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A Call for Sanity in NoSQL
Nathan Marz discusses building NoSQL-based data systems that are scalable and easy to reason about.
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Real Data Science at NASA
Chris Mattmann envisions data science by integrating science software into rapid data production systems using cloud computing and open source software.
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Ember-Data, the Way Forward
Igor Terzic presents several cases where Ember Data is used in production, and outlines some of the features that are intended to be included in the future.
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Ember.js Advanced Patterns
Paul Chavard discusses advanced techniques for building large EmberJS applications with Ember Data.
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Deploying Machine Learning and Data Science at Scale
Nick Kolegraff discusses common problems and architecture to support all the phases of data science and how to start a data science initiative, sharing lessons from Accenture, Best Buy, and Rackspace.
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