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.

Growing as a company involves a myriad of elements, but ultimately, it comes down to the practices and routines that teams have. These habits have a great impact on boosting team performance and engagement, which helps the company move ahead together. Fostering a high-performance culture means creating a space where team members do their best because they are engaged, feel valued, and keep learning.

It’s 2024. In the last decade, we’ve seen manual file sorting become ETL, then ETL became ELT and ELT became dbt. But we still use spreadsheets in our boardrooms, and flat files are still filling critical business workflows.

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.

Exploring fraud detection with automated data integration in a cloud data warehouse: part one of two.