Systems | Development | Analytics | API | Testing

Snowflake Workloads Explained: Data Engineering

Nov 2, 2020 By Snowflake In Snowflake
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.
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Snowflake Workloads Explained: Data Applications

Nov 2, 2020 By Snowflake In Snowflake
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.
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Snowflake for Marketing Analytics

Nov 2, 2020 By Snowflake In Snowflake
Identify deeper insights with 360° customer views, create relevant messaging and offers, and produce much higher marketing ROI. Snowflake’s platform virtually eliminates data silos to create a single repository for a single copy of your data. As a result, marketing teams extract deep insights and deliver timely, relevant and consistent customer messaging and offers.
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10 Best Practices Every Snowflake Admin Can Do to Optimize Resources

Oct 30, 2020 By David A. Spezia In Snowflake

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.

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