I am looking forward to attending a nearby Snowflake Data for Breakfast session next week to learn more about how Snowflake customers are uniting siloed data, working and collaborating seamlessly across multiple clouds, and other ways they are leveraging Snowflake in exciting and innovative use cases.
As a former Data Virtualization CMO, I am impressed by the scale of this marketing program. More than one hundred cities around the globe! That certainly demonstrates the value that Snowflake provides its customers today.
But value is like an excellent meal. When you have a great one, why not top it off with a nice dessert?
Keebo delivers high value for dessert
Where can Snowflake users find a tasty, high-value dessert that complements their Snowflake environment?
The answer is with Keebo’s fully automated Snowflake optimizer which helps companies increase Snowflake usage while decreasing their costs by 20-70%.
Fully automated sounds pretty tasty. And that level of savings sounds pretty valuable. Want to know more?
Keebo optimizer for Snowflake at a glance
Here are three things to know about the Keebo Snowflake Optimizer.
- It really is fully automated. Not only does it automatically optimize warehouse size, clustering, and memory without impacting performance, it also continues to find additional savings by learning and adjusting to workload changes in real time.
- It sets up super fast. Setup takes just minutes and results occur within 24-48 hours. Plus it is non-invasive, with no changes needed to your Snowflake warehouse or applications.
- It is highly user friendly. Using only telemetry metadata, it never accesses user data. It is easy to adjust to support complex scenarios and schedules. And every action is fully auditable and visible via KPI reports.
Ready for a taste test?
An easy way to get a taste of Keebo Snowflake optimization is to check out our webinar, Optimize Snowflake to Do More with Fewer Credits.
In this webinar, you will learn what you need to know about Snowflake optimization, and hear how one company cut Snowflake costs by 70% and another increased Snowflake usage by 25% while cutting Snowflake costs by 21%.