Analytics

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.

Improve Your Website's SEO with Ahrefs Webmaster Tools

Today SEO is much more than just finding high converting keywords for better ranking. Most marketers and content writers nowadays rely on different strategies to stay in the game. Imagine handling such intricate tasks manually or shuffling through several tools daily to get this done. Sounds hectic, right? But what if we told you, there’s a single package out there to make your work easier.

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.