InfoQ Homepage Data Analysis Content on InfoQ
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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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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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Applying Big Data
Graeme Seaton discusses the drivers behind Big Data initiatives and how to approach them using the vast amounts of data available.
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Creating Customer-Centric Products Using Big Data
Kriti Sharma talks about how Barclays is solving some of the toughest big data challenges in financial services using scalable, open source technology.
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Building a Predictive Intelligence Engine
Viral Bajaria explains a formula for reaching the B2B buyer early in the sales cycle by tying together billions of rows of customer data and overlaying predictive intelligence technology.
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Hypermedia Web API as a Network of Data
Todd Brackley discusses accessing the “network of data” through a RESTful hypermedia API, exposing it to developers, testers, analysts and clients.
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Big-Data Analytics Misconceptions
Irad Ben-Gal discusses Big Data analytics misconceptions, presenting a technology predicting consumer behavior patterns that can be translated into wins, revenue gains, and localized assortments.
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Understanding Real-time Conversations on Facebook
Janet Wiener discusses using a data pipeline and graphic visualizations to extract and analyze the Chorus – the aggregated, anonymized voice of the people communicating on Facebook - in real time.
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Real-time Stream Computing & Analytics @Uber
Sudhir Tonse discusses using stream processing at Uber: indexing and querying of geospatial data, aggregation and computing of streaming data, extracting patterns, TimeSeries analyses and predictions.
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Rethinking Streaming Analytics for Scale
Helena Edelson addresses new architectures emerging for large scale streaming analytics based on Spark, Mesos, Akka, Cassandra and Kafka (SMACK) or Apache Flink or GearPump.
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Insights from History of Rock Music via Machine Learning
Ali Kheyrollahi uses clustering and network analysis algorithms to analyze the publicly available Wiki data on rock music to find mathematical relationship between artists, trends and subgenres.
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Supercharging Operations and Analytics: Using Spring XD to Support Analytics and CEP
Joseph Paulchell discusses the journey from batch-oriented processes using databases to a real-time data streaming solution and the significant benefits achieved as well as the challenges encountered.