Systems | Development | Analytics | API | Testing

Avoiding Digital Disaster: The 5 Things You May be Doing Wrong

If your cholesterol were to become too high, would you ignore the test results? Probably not, because when it comes to healthcare, many of us recognize that a data-driven approach helps keep a person healthy. So why is it that so few business decisions — perhaps fewer than half — are made using quantitative data? Sounds like some pretty risky disregard for corporate well-being.

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.

Docker Tutorial: Get Going From Scratch

Docker is a platform for packaging, deploying, and running applications. Docker applications run in containers that can be used on any system: a developer’s laptop, systems on premises, or in the cloud. Containerization is a technology that’s been around for a long time, but it’s seen new life with Docker. It packages applications as images that contain everything needed to run them: code, runtime environment, libraries, and configuration.