Gaming Analytics Platform with Kir Titievsky, Eric Anderson, and Tino Tereshko

Analytics is an essential part of many platforms, but it is specially important for gaming. Today we discuss how Google Cloud makes analytics simpler and super powerful. Kir Titievsky from Google Cloud Pub/Sub, Eric Anderson from Google Cloud Dataflow, and Tino Tereshko from Google BigQuery will tell your co-hosts Francesc and Mark how those three products get together to power an amazing analytics solution for gaming.

About Kir

Kir Titievsky is product manager on Google Cloud Pub/Sub which helps users build analytics pipelines & integrate services, massive and small. He has come to GCP after building mobile enterprise apps for Googlers as well as products for advertising & media agencies at DoubleClick. Before Google, Kir designed advertising recommendation engines as a data scientist. Kir once took a detour to get a PhD in Chemical Engineering from MIT.

About Eric

Eric Anderson is a product manager on Dataflow, a stream and batch data processing service. Before Dataflow, he started a growth analytics team in Google Cloud. Previously he worked at AWS and GE. Eric holds an engineering degree from the University of Utah and MBA from Harvard.

About Tino

Tino Tereshko is a Technical Program Manager for BigQuery, the world’s only serverless analytics Data Warehouse. Before joining the BigQuery team, Tino worked with strategic cloud customers as a Solutions Architect. Prior to Google, Tino worked in stream processing, financial analytics, and even spent some time as a quant developer.

Cool thing of the week

• BigQuery 1.11, now with Standard SQL, IAM, and partitioned tables! post

Interview

• Building a Mobile Gaming Analytics Platform - a Reference Architecture docs

• Google Cloud Pub/Sub docs
• Google Cloud Dataflow docs
• Google BigQuery docs
• ETL: Extract, transform, load Wikipedia
• Apache Beam Project docs
• MapReduce: Simplified Data Processing on Large Clusters research paper
• The Dataflow Model: A Practical Approach to Balancing Correctness, Latency, and Cost in Massive-Scale, Unbounded, Out-of-Order Data Processing research paper
• Pushing the Limits of BigQuery video

Question of the week

• Google BigQuery Public Datasets docs
• The first TB is free! pricing