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Introducing Query Profile Insights with Snowflake

Behind the scenes at Astrato we work closely with our partners to give you a smooth and user friendly data visualization experience. We are a trusted Snowflake Technology Partner, and we work closely with Snowflake to help users get even more from their data analytics.

Purpose-built for Snowflake’s Data Cloud, Astrato’s no-code framework for Data Apps delivers you data analytics insights with the speed, security and scalability of your data Cloud. This means seamless live query data and better business decisions today and into the future! 

In this blog, we’re going to discuss an exciting recent example of the power of our partnership – introducing Snowflake’s powerful new table function and explaining how Astrato harnesses it for an easier, more intuitive user experience.

Snowflake’s new table function helps you optimize query performance

Query performance is a key component to accelerating speed to insight in the most efficient way possible. But optimizing query performance can be challenging.

To help users increase query efficiency, Snowflake recently introduced a new table function, GET_QUERY_OPERATOR_STATS, which returns statistics about individual operators within a query. With this new function, a data expert may detect inefficiencies and suggest improvements. For example, they may notice a warning of “memory spilling,” and they may decide to fix the problem by changing the size of the warehouse. This is an invaluable asset, but Astrato users are not always data experts! 

And that’s where Query Profile Insights comes in. 

Query Profile Insights detects and identifies query inefficiencies, without the need to code

Warnings and auto-generated results that can be sent to your Snowflake administrator

At Astrato, we created Query Profile Insights to help you harness Snowflake’s powerful new function – without the need to code – by creating a unique, intuitive interface that gives red warnings when a query deserves attention. We identified four common types of query inefficiency – Cartesian, Union, Memory, and Pruning – and when a red warning appears, the user can simply press “copy result,” and send it on to their Snowflake administrator for further evaluation and action. We chose to display these four indicators because Snowflake specifically highlights them as examples of common mistakes that cause query inefficiency. 

Introducing Query Profile Insights

Know how many rows have been scanned, and how many credits have been used for informed cost estimates

In addition to giving you a warning, Astrato’s Query Profile Insights panel also shows the number of rows scanned – this is not to be confused with the result data. As you can see in the image above, the final result of this particular query is five rows. But to achieve that result, Snowflake had to read 1.65M rows!

Finally, let’s talk about credits. You will be told how many credits you’ve used after you’ve made a query. This is like receiving a message detailing the total cost of your conversation after making a long international call. With this information, you can estimate how much future calls are going to cost you.

This is one of many efforts that Snowflake and our team at Astrato are making to ensure that all users can save time and money (and CPU resource!) with the most efficient queries possible. 

Get started with Astrato

Ready to explore this exciting new feature? Getting started with Astrato is easy. We offer a simple and transparent pricing structure that scales with your business, and our team of friendly product experts can guide you through the process of building your ideal BI solution. Book a demo with us today to find out more.

Also, if you’re looking for more product news keep an eye out for this month’s roadmap update, or visit our roadmap page, in the meantime.