InfoQ Homepage Big Data Content on InfoQ
-
How Predictive Analytics Boosts the Customer Experience at the Georgia Aquarium
Beach Clark talks about the technological and cultural challenges of turning data science into a vital part of the business model at Georgia Aquarium.
/presentations/big-data-georgia-aquarium/en/mediumimage/BeaBIG.JPG)
-
Overview of Artificial Intelligence and Its Use in Analyzing “Voice of Cancer Patients”
Alok Aggarwal overviews Artificial Intelligence and discusses a use case, “Voice of Cancer Patients” that uses ML and NLP algorithms to analyze unstructured text written by cancer patients.
/presentations/ai-ml-nlp-cancer/en/mediumimage/AloBIG.JPG)
-
Solving Business Problems with Data Science
The panelists discuss how Data Science can help solve various problems for business.
/presentations/data-science-business-panel/en/mediumimage/Panelbig.jpg)
-
Hydrator: Open Source, Code-Free Data Pipelines
Jonathan Gray introduces Hydrator, an open source framework and user interface for creating data lakes for building and managing data pipelines on Spark, MapReduce, Spark Streaming and Tigon.
/presentations/hydrator/en/mediumimage/Jonbig.JPG)
-
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.
/presentations/ml-predictive-analytics-engine/en/mediumimage/Alibig.JPG)
-
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.
/presentations/wikipedia-apache-spark/en/mediumimage/Sambig.JPG)
-
Applying Big Data
Graeme Seaton discusses the drivers behind Big Data initiatives and how to approach them using the vast amounts of data available.
/presentations/big-data-initiatives/en/mediumimage/Grabig.JPG)
-
Apache Beam: The Case for Unifying Streaming APIs
Andrew Psaltis talks about Apache Beam, which aims to provide a unified stream processing model for defining and executing complex data processing, data ingestion and integration workflows.
/presentations/apache-beam/en/mediumimage/Andbig.JPG)
-
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.
/presentations/barclays-big-data/en/mediumimage/Kribig.JPG)
-
Server-Less Design Patterns for the Enterprise with AWS Lambda
Tim Wagner defines server-less computing, examines the key trends and innovative ideas behind the technology, and looks at design patterns for big data, event processing, and mobile using AWS Lambda.
/presentations/serverless-computing/en/mediumimage/Timbig.JPG)
-
Predicting the Future: Surprising Revelations trom Truly Big Data
Pushpraj Shukla discusses how Microsoft Bing predicts the future based on aggregate human behavior using one of the largest scale data sets, and recent progress in large scale deep learnt models.
/presentations/bing-predict-future/en/mediumimage/Pubig.JPG)
-
Netflix Keystone - How We Built a 700B/day Stream Processing Cloud Platform in a Year
Peter Bakas presents in detail how Netflix has used Kafka, Samza, Docker, and Linux to implement a multi-tenant pipeline processing 700B events/day in the Amazon AWS cloud.
/presentations/netflix-keystone/en/mediumimage/Pebig.JPG)