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Snowflake

Snowflake Workloads Explained: Data Engineering

Snowflake streamlines data engineering, while delivering performance and reliability. Learn how with Snowflake, data engineers can spend little to no time managing infrastructure, avoiding such tasks as capacity planning and concurrency handling. Instead, they can focus on more value-add activities towards delivering your data.

Snowflake Workloads Explained: Data Applications

Snowflake’s platform powers applications with virtually unlimited performance, concurrency, and scale. Launch new features faster with simplified data pipelines and improved engineering efficiency. Delivered as a service, Snowflake handles the infrastructure complexity, so you can focus on innovating with the data applications you build.

10 Best Practices Every Snowflake Admin Can Do to Optimize Resources

As we covered in part 1 of this blog series, Snowflake’s platform is architecturally different from almost every traditional database system and cloud data warehouse. Snowflake has completely separate compute and storage, and both tiers of the platform are near instantly elastic. The need to do advanced resource planning, agonize over workload schedules, and prevent new workloads on the system due to the fear of disk and CPU limitations just go away with Snowflake.

The New Face of Secure Data Collaboration: Transforming Government with the Data Cloud

The push to embrace cloud-based technologies has undoubtedly transformed IT infrastructures at every level of government. Federal, state, and local agencies have made significant strides in modernizing how data is collected, stored, and analyzed, all in service of their mission and in fulfillment of strategic IT mandates.