Since announcing our new interface back in July, our goal has been to make it easier for BigQuery users and their teams to uncover insights and share them with teammates and colleagues. Whether you’re a veteran or brand new to BigQuery, we wanted to highlight some of the major improvements we’ve made to the interface in the past five months. Some of this functionality was previously available in the classic UI, while other elements are totally new. Let’s take a closer look.

Google BigQuery is a serverless enterprise data warehouse tool that’s designed for scalability. We built BigQuery to be highly scalable and let you focus on data analysis without having to take care of the underlying infrastructure. We know BigQuery users like its capability to query petabyte-scale datasets without the need to provision anything. You just upload the data and start playing with it.

As more and more businesses turn to advanced data analytics to help them make smarter decisions, run real-time analytics, and improve business operations, an increasing number are modernizing their data warehouses to make it all possible. For many businesses, knowing how to modernize means understanding where their data warehouse sits on the spectrum between traditional and cutting edge. To help, we collaborated with TDWI to offer the data warehouse maturity assessment.

There are plenty of trends and hot topics in the enterprise technology market today. One common area we hear about from users is that there’s a lot of data to collect, manage, and analyze. And whatever industry you’re in, you probably want to do something more with your data. We built BigQuery, one of the important tools in the Google Cloud Platform (GCP) arsenal, to provide serverless cloud data warehousing and analytics with built-in machine learning to meet modern data needs.

As more and more businesses look to the cloud to store and manage their data, an increasing number are embracing BigQuery as their serverless, highly scalable, enterprise data warehouse.