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Google BigQuery

How BuzzFeed Built A Great Data Experience Using BigQuery and Looker (Cloud Next '18)

This talk will focus on how BigQuery and Looker allowed a small data team at Buzzfeed to manage the data needs of 800 users, and how migrating from AWS Redshift to BigQuery gave us the performance we needed to allow interactive querying of large datasets by non-technical people.

Bridging the gap between data and insights

Today, we want to share a number of updates that will make data analytics easier and more accessible to all businesses. Our goal is to help you focus on data analysis instead of infrastructure management, give you the freedom to orchestrate workloads across clouds, use machine-learning in a way that's integrated with your data analytics operations, and take advantage of open source data processing innovation.

BigQuery in June: a new data type, new data import formats, and finer cost controls

This is the first installment in a monthly review of recently-released BigQuery features. While our rather active release notes do contain concise but actionable information, we’ve heard from some of our users that they’d love a little more information on these updates and what they mean in a bigger picture. This month, we present a number of practical new features, primarily focused on data types and data file formats.

Transform publicly available BigQuery data and Stackdriver logs into graph databases with Neo4j

In today’s blog post, we will give a light introduction to working with Neo4j’s query language, Cypher, as well as demonstrate how to get started with Neo4j on Google Cloud. You will learn how to quickly turn your Google BigQuery data or your Google Cloud logs into a graph data model, which you can use to reveal insights by connecting data points.

BigQuery at speed: new features help you tune your query execution for performance

BigQuery is a managed analytics service that provides advanced cloud data warehouse capabilities with a diverse set of features. One of BigQuery’s most significant differentiators is its distributed analytics engine, which transforms your SQL queries into complex execution plans, dispatching them onto our execution nodes to promptly provide insights into your data.

How to process weather satellite data in real-time in BigQuery

Since the 1960s, scientists have been forecasting the weather using satellite-captured imagery. Although access to these satellite feeds used to be reserved just for meteorologists, these days anyone can jump online to find current satellite footage for their area. But what if you wanted to take things a step further? Maybe you’re curious about the history of weather events, or want to create a real-time feed for where you live.