These are the essential tips for querying GitHub’s ongoing history with Snowflake. Use these tips to explore and uncover insights within this 17 terabyte dataset, while avoiding common mistakes. GH Archive is now available free in the Snowflake Marketplace — so let’s get started. — Before joining Snowflake, I authored many posts on ways to analyze Github with BigQuery. Now that the GH Archive dataset is available in Snowflake (thanks to Cybersyn), I’m happy to share with you my top tips to enable your discovery journey.

Now that dbt has made Python a seamless option within your SQL pipelines, it’s super cool to see how they made this possible with Snowflake. That’s what this post is about. Are you ready to try this out? — What is dbt Before we start, let me explain dbt — especially for data engineers that still have not worked with it: “dbt” is a tool that helps us manage all the transformations we do with SQL to data in our databases.

Losing weight can be a challenge, especially when surrounded by unlimited delicious food. Here’s how a data focused approach helped me achieve sustainable results without giving up my favorite foods or resorting to extreme measures. — After a lifelong struggle with weight issues, I am happy to share the story of how I succeeded at losing a significant amount of fat in a healthy and controlled way. This post outlines the changes I made, and the power of utilizing data to track my progress and make…

An overview of why Django and Snowflake are important to each other, how to build a simple application with the new open source Django connector using data from Snowflake, and how the connector is keeping up with the latest updates. — Snowflake announced that the Snowflake Connector for Django is now updated and available in Snowflake Labs on GitHub. This is great news for everyone that has already connected Django to Snowflake— and for anyone that is about to discover the possibilities behind this.

We can use the Stack Overflow data dumps to analyze the health of any tags and much more. But before analyzing, let’s load this data while showing off the Snowflake abilities to parse XML and files compressed with exotic formats. — Imagine an ideal world Before joining Snowflake I wrote many posts analyzing Stack Overflow’s data — now it’s time for me to share how you can load these dumps into your account.

When replicating data to multiple regions, cloud egress costs can be pretty significant. So this is exciting: Now Snowflake can use Cloudflare R2 as external storage for tables— featuring cheap storage and zero egress fees. Here’s how. — Update May 2023: Now this is an official partnership between Cloudflare and Snowflake Use Snowflake with R2 to extend your global data lake R2 is the ideal object storage platform to build data lakes. It's infinitely scalable, highly durable (eleven 9's of…blog.cloudflare.com

Redundant join elimination is a new feature that helps some SQL queries run way faster. To get these benefits, you will need to give some hints to Snowflake. Let’s figure out these constraints here. — A quick review of redundant join elimination Sometimes people (and tools) write joins in SQL that end up being redundant. If eliminated these queries could run significantly faster, saving time and complexity. Snowflake is ready to do this automatically, but to do this safely Snowflake might need some extra information from you.

Let’s find out what the new `memoizable’ SQL UDFs are, their effects, and limitations. Then let’s put them to work with an example that shows how to improve the performance of complex security policies. — The effects of `memoizable` Memoizable UDFs behave like smart session variables that remember the results of the UDF even beyond a session. These UDFs will only recompute the results if the underlying data changes, leading to improved performance as results are not computed repeatedly.

Snowflake users can finally dig deep into query stats with this new function. This data was only available in the query profile visualization, and now you can get it in your SQL world with GET_QUERY_OPERATOR_STATS(). Let’s review the new function, and how to use it to get deeper insights while benchmarking. — The old ways Previously you could find deep stats only on the query profile visualization UI: