BigQuery and Social Data

Mar 30, 2015 · Oxfordshire, United Kingdom

A special double header, in conjunction with GDG Oxford.


Querying massive datasets can be time consuming and expensive without the right hardware and infrastructure. Google BigQuery solves this problem by enabling super-fast, SQL-like queries against append-only tables, using the processing power of Google's infrastructure. 

That's the claim - how true is it in practice?

To talk about it we have Javier Ramirez, a Google Developer Expert on the Cloud Platform, Web developer, daydreamer and “all around happy person”. Founder of and - Datawaki collects technical and business data from your application or from your devices and lets you run interactive queries, generate reports and get real-time alerts. and Teowaki improves communication between developers and helps share technical information, best practices, gossip and lifehacks with your developer friends.

Teowaki big data architecture combines Redis + BigQuery + Google Apps Scripts for analytics. Datawaki architecture, combines Nginx + Logstash + Redis + BigQuery + Neo4j.

A software engineer (18 years in IT) with a strong focus on the web (15 years building web applications). Experience building web applications using Ruby on Rails with data stores and complementary technologies and in technical training, content management, e-commerce and online banking using Java, PHP and C++. Also University lecturer on Software Engineering and Programming Languages.

Javier loves talking at tech conferences. Subjects covered include Big Data (AWS + Google Bigquery), Redis, Ruby on Rails, API usability, REST web services, hypermedia APIs, agile development, SEO, analytics, CSS frameworks, game development and software engineering.

Social Data Wrangling & Classification with Machine Learning
Tim Budden, Director of Data Science, DataSift

Tim Budden heads up Data Science at DataSift, where on a daily basis he wrestles with huge quantities of unstructured social data, extracting value for customers and guiding DataSift feature development.

Event organizers
  • Data Science Oxford

    We are a community of data scientists, technologists and analysts who work with data. This Meetup discusses the tools, methods and technologies used to analyse large scale data (big data), obtain predictive insight, and exploit business opportunities from data products. We talk about topics like: big data analytics, distributed data analytics, Pig, Hive, data mining, machine learning, scalabl...

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