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.

I am very excited to introduce Talend Data Streams, a brand new, cloud-native application that enables you to get streaming data integrations up and running in minutes all while providing unparalleled portability powered by Apache Beam.

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.

With the growing adoption of cloud-based IT infrastructures, the proliferation of mobile and IoT devices, and the rise of social media, companies of all sizes, across all industries are amassing huge quantities of data in differing variety, velocity, veracity and validity.

In the past few years, there has been a shift in the data industry, leading to the emergence of a new category of data citizens: the ‘ad hoc’ or ‘citizen’ integrators. With these new personas adding to the (already long) list of data workers having access to corporate information, companies are needing to re-think the way they approach their data security and data governance strategies.