Systems | Development | Analytics | API | Testing

In the buildup to this week’s World Economic Forum Annual Meeting in Davos, Switzerland, the talk of polycrisis becoming permacrisis painted a picture of impending doom. These terms have been used to describe the global condition today, citing the “cascading and connected crises” triggered by war and geopolitics, economic uncertainty, and environmental concerns, and their persistence.

Imagine seamlessly integrating your Google Analytics data with Snowflake, allowing you to combine it effortlessly with other key sources like CRM, ERP, social media metrics, email campaign data, and whatever data sources compose the full scope of your data estate. The good news is that it’s possible with the native Snowflake Connector for Google Analytics, now available in public preview.

As we assess the technological landscape for the new year, one of the only guarantees is that technology will continue to evolve. Cloud migration and support are top-of-mind for worldwide organizations–this year, cloud computing is forecast to surpass $1 trillion worldwide for the first time. Cloud-based ERPs reduce operating costs, can help automate processes, and provide finance teams with greater autonomy.

A key benefit of the Snowflake Data Cloud is the elimination of data silos. Fundamental to this outcome is the ability of customers to operate and collaborate globally. To support this, the Data Cloud was designed to provide customers with the same product experience—including security and governance capabilities — across multiple cloud regions with the three major cloud providers: AWS, Azure, and Google Cloud.

In this article, we will walk you through the process of implementing fine grained access control for the data governance framework within the Cloudera platform. This will allow a data office to implement access policies over metadata management assets like tags or classifications, business glossaries, and data catalog entities, laying the foundation for comprehensive data access control.

Snowflake data engineers are under enormous pressure to deliver results. This data sheet provides more context about the challenges data engineers face and how Unravel helps them address these challenges. Specifically, it discusses: With Unravel, Snowflake data engineers can speed data pipeline development and analytics initiatives with granular and real-time cost visibility, predictive, predictive spend forecasting, and performance insights for their data cloud.