Improve data management with new Google updates to the BigQuery platform

Google is making changes to how teams work with their data. Today at its annual Cloud Next conference, the Internet giant announced updates to its data warehouse; BigQuery unveiled to make it easier for teams to work with their data. These improvements include a seamless experience for connecting data and workloads. Google also plans to use artificial intelligence to analyze the data stored on the platform and increase the productivity of teams by providing valuable insights.

“These innovations help organizations realize the potential of data and artificial intelligence to realize business value, from personalizing customer experiences, improving efficiency,” said Gerrit Kazmeier, vice president and general manager of databases, data analytics and business intelligence at Google Cloud. supply chain and help reduce operating costs to help increase revenue.” This information was shared in a blog post by Google Analytics.

However, it should be noted that most of these features are still in preview and not generally available to customers.

Integrated experience with BigQuery Studio

Google has introduced a new feature called BigQuery Studio in its BigQuery platform. BigQuery Studio is an integrated interface that enables users to work with large amounts of data for tasks such as data engineering, analytics, and predictive analytics. It provides a single environment where users can perform these activities.

In the past, data teams had to use multiple tools to perform various tasks such as managing data warehouses, data lakes, governance, and machine learning. This process was time-consuming and reduced productivity. However, Google has introduced BigQuery Studio, a platform that allows these teams to access all these tools in one place. BigQuery Studio allows them to easily discover, prepare and analyze their datasets, as well as run machine learning tasks on them.

“BigQuery Studio provides a convenient and integrated interface for data teams to analyze their data in Google Cloud, enabling them to use SQL, Python, Spark and other languages,” a company spokesperson told VentureBeat. Edit the programming. This makes it easier to perform large-scale analysis. “This eliminates the need for data workers to switch between different tools, and by having all these capabilities in one place, it simplifies their work and enables them to achieve faster results without the need for additional infrastructure management costs.”

The offer is now available in preview and is currently being tested by several companies, including Shopify. Kazmeier also said that Google is adding advanced support for game source formats like Hudi and Delta Lake in BigLake, as well as introducing performance acceleration for Apache Iceberg. Additionally, users can now leverage cross-cloud views and cross-cloud joins in BigQuery Omni, allowing them to analyze and train on data without the hassle of moving it around.