Pablo is a passionate software engineer who enjoys solving complex problems, and devising simple solutions. He works at Shine Technologies and he is part of a team that uses BigQuery and Dataflow to solve challenging and complex data processing business requirements.
Pablo has extensive experience building software solutions mainly in Java, as well as client-server applications.
Pablo considers that scalability and performance are paramount to developing a great solution, and that is why he has been using Dataflow and BigQuery to bring these solutions to reality.
Pablo enjoys spending time with his family and friends as well as playing his guitar. He also likes experimenting with mobile development and reading scientific stuff.
YOW! Data 2016 Sydney
Stomping on Big Data using Google’s BigQuery
Managing infrastructure, worrying about scalability, and waiting for queries to finish executing are some of the biggest challenges when working with massive volumes of data. One solution is to outsource the heavy lifting to someone else, thereby allowing you to spend more time on actually analyzing, and drawing insights out of your data. It other words, look to harnessing the cloud to solve big data problems.
BigQuery is a SaaS tool from Google that is designed to make it easy for us to get up and running without the need to care about any operational overheads. It has a true zero-ops model. BigQuery’s bloodline traces back to Dremel, which was the inspiration for many open sources projects such as Apache Drill. Using a massively parallel processing, tree, and columnar storage architecture, your queries will run on thousands of cores inside Google’s data centres without you spinning up a single VM. This talk will cover its core features, cost model, available APIs, and caveats. Finally, there will be a live demo of BigQuery in action.