The Data Warrior

Changing the world, one data model at a time. How can I help you?

Do Not Follow…Leave a Trail!

Do not follow where the path may lead…

Go instead where the is no path and leave a trail

— Ralph Waldo Emerson

Good advice in general.

I am very happy to be working for Snowflake Computing (@snowflakedb) and our CEO Bob Muglia (@bob_muglia) where we are forging the path for Elastic Data Warehousing (#ElasticDW)

We (Snowflakes) had a great time at Data Day Texas (#DDTX16) in Austin over the weekend. I think it is fair to say people are excited to see the trail we are blazing.

Have a great week!

Kent

The Data Warrior and Snowflake Evangelist

P.S. You can find the slides from my Data Day presentation on my LinkedIn profile or at slideshare.net/kgraziano

Better Data Modeling: Customizing Oracle Sql Developer Data Modeler (#SQLDevModeler) to Support Custom Data Types

On a recent customer call (for Snowflake), the data architects were asking if Snowflake provided a data model diagramming tool to design and generate data warehouse tables or to view a data model of an existing Snowflake data warehouse. Or if we knew of any that would work with Snowflake.

Well, we do not provide one of our own – our service is the Snowflake Elastic Data Warehouse (#ElasticDW).

The good news is that there are data modeling tools in the broader ecosystem that you can of course use (since we are ANSI SQL compliant).

If you have read my previous posts on using JSON within the Snowflake, you also know that we have a new data type called VARIANT for storing semi structured data like JSON, AVRO, and XML.

In this post I will bring it together and show you the steps to customize SDDM to allow you to model and generate table DDL that contain columns that use the VARIANT data type.

Read the details of how I did it here on my Snowflake blog:

Snowflake SQL: Customizing Oracle Sql Developer Data Modeler (SDDM) to Support Snowflake VARIANT – Snowflake

Enjoy!

Kent

The Data Warrior

P.S. If you are in Austin, Texas this weekend, I will be speaking at Data Day Texas (#DDTX16). Snowflake will have a booth there too, so come on by and say howdy!

Snowflake SQL: Making Schema-on-Read a Reality (Part 2)

This is the 2nd of my articles on the Snowflake blog.

In the first article of this series, I discussed the Snowflake data type VARIANT, showed a simple example of how to load a VARIANT column in a table with a JSON document, and then how easy it is to query data directly from that data type. In this post I will show you how to access an array of data within the JSON document and how we handle nested arrays. Then finally I will give you an example of doing an aggregation using data in the JSON structure and how simple it is to filter your query results by referring to values within an array.

Check out the rest of the post here:

Snowflake SQL: Making Schema-on-Read a Reality (Part 2) – Snowflake

Enjoy!

Kent

The Data Warrior

#DataWarrior 2015 in review

Happy New Year again everybody!

Shoutout to Jeff Smith for again being the #1 real person that I actually know who referred people to my blog via his blog. If you don’t already, please add ThatJeffsSmith to your reading list.

The WordPress.com stats helper monkeys prepared a 2015 annual report for me.

Here’s an excerpt:

Madison Square Garden can seat 20,000 people for a concert. This blog was viewed about 69,000 times in 2015. If it were a concert at Madison Square Garden, it would take about 3 sold-out performances for that many people to see it.

Click here to see the complete report.

Cheers!

Kent

The Data Warrior and Snowflake Evangelist

Happy 2016!

Happy New Year

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