InfoQ Homepage Data Analytics Content on InfoQ
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Speed of Apache Pinot at the Cost of Cloud Object Storage with Tiered Storage
Neha Pawar discusses how to query data on the cloud directly with sub-seconds latencies, diving into data fetch and optimization strategies, challenges faced and learnings.
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Evolving Analytics in the Data Platform
Blanca Garcia-Gil discusses the BBC’s analytics platform architecture, the failure modes they designed for, and the investigation of the new unknowns and how they automated them away.
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Putting the Spark in Functional Fashion Tech Analytics
Gareth Rogers shows how his team used Clojure to provide a solid platform to connect and manage an AWS hosted analytics pipeline and the pitfalls they encountered on the way.
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Gimel: PayPal’s Analytics Data Platform
Deepak Chandramouli introduces and demos Gimel, a unified analytics data platform which provides access to any storage through a single unified data API and SQL.
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A Cloud-centric Ecosystem Approach to Ease IoT Development
Yujing Wu discusses two use cases of a cloud-based IoT ecosystem that enables IoT device communication across silos and interoperability across different vendors.
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Enabling High Performance Real-time Analytics for IoT Environments
Mahish Singh discusses how to use methodologies during design, development, deployment and operation for delivery of analytics platforms which offer real-time SLAs.
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Scaling up Near Real-Time Analytics @Uber &LinkedIn
Chinmay Soman and Yi Pan discuss how Uber and LinkedIn use Apache Samza, Calcite and Pinot along with the analytics platform AthenaX to transform data to make it available for querying in minutes.
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Stream Processing & Analytics with Flink @Uber
Danny Yuan discusses how Uber builds its next generation of stream processing system to support real-time analytics as well as complex event processing.
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Elastic Data Analytics Platform @Datadog
Doug Daniels discusses the cloud-based platform they have built at DataDog and how it differs from a traditional datacenter-based analytics stack, pros and cons and the tooling built.
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Streaming Live Data and the Hadoop Ecosystem
Oleg Zhurakousky discusses the Hadoop ecosystem – Hadoop, HDFS, Yarn-, and how projects such as Hive, Atlas, NiFi interact and integrate to support the variety of data used for analytics.
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Scaling Counting Infrastructure @Quora
Chun-Ho Hung and Nikhil Garg discuss Quanta, Quora's counting system powering their high-volume near-real-time analytics, describing the architecture, design goals, constraints, and choices made.
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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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