Getting to Know Snowflake Snowsight — Snowflake’s Interactive SQL Editor
Snowflake Data Cloud, a true Software-as-a-Service (SaaS) offering, is available on Azure, AWS, and GCP. A feature that’s been around since I’ve been working with Snowflake is the classic Console UI/ Worksheet feature which provides a web interface to submit, execute, and view results of SQL queries in Snowflake. It’s a bit limited though on providing insights about the data to perform analytical tasks.
In order to provide a better user experience, Snowflake launched the next generation of its Analytics UI — Snowsight. Snowsight accelerates a user’s query scripting and data visualization activities.
I am using Snowsight every day and it’s helping me identify outliers and quality issues with the initial data load. In addition, the autocomplete feature is helping me to write queries even faster.
If you are a Snowflake user (data engineer, analyst, business user) and have not yet explored Snowsight then definitely read on. While Snowsight is currently in preview, this blog post will walk you through the exciting features of Snowsight.
What is Snowsight?
Snowsight — Interactive SQL editor with charts.
Snowsight, the SQL Worksheets replacement, is designed to support data analyst activities. Snowsight is available in the new Snowflake web interface.
How can you access Snowsight?
- By clicking on ‘Preview App’ from the Snowflake UI.
- By using this URL — https://app.snowflake.com/
Key Features of Snowsight
Getting Started
Once you open the Snowsight web interface, you get a notification to import your worksheets from the Classic Console. You can also start with creating new worksheets by clicking on the ‘Worksheet’ button.
- Import existing worksheets from the Classic Console — You can import existing worksheets from the Classic Console and start executing queries from Snowsight.
2. Organize the worksheets in folders — If you have multiple worksheets, it’s always good to organize them in folders. The screenshot below is showing worksheets in the ‘Project 1’ folder.
3. Collaboration — Snowsight allows you to share folders, worksheets, and dashboards with colleagues which makes working together much easier.
Worksheets
4. Autocomplete — Auto-complete speeds up writing queries and gives suggestions about schemas, column names, and SQL functions. The two screenshots below are showing the autocomplete feature of Snowsight.
5. Automatic contextual statistics — On successful execution of SQL query in Snowsight, the results pane shows contextual statistics for rows, columns, or data ranges. These statistics are automatically generated for all column types and provide useful data insights. It provides instant access for the selected column to averages, sums, and more along with histograms to find outliers and quality issues. In the screenshot below, the highlighted area in blue is showing automatic contextual statistics generated for ‘date’, ‘num trips’, and ‘avg duration’ columns.
6. Worksheet history — Every version of your SQL script is automatically logged once you run it and the full history is available from a dropdown.
7. Custom filter — Custom filters are special keywords that resolve as a subquery or list of values. Your role must have permission to create the custom filter.
:daterange and :datebucket system filters are available to all roles. In a Snowsight worksheet, when a colon (:) is typed, the autocomplete functionality lists all possible custom filter SQL keywords. Once a custom filter is selected from that list, the relevant filter appears at the top left of the screen.
In the screenshot below, the daterange system filter is used in the where clause. When :daterange is typed in the query, all date range filters are enabled. Based on the selection of date range filters, query results are refreshed.
8. Chart — After executing a query, click on the ‘Charts’ tab. For each query result, a chart is automatically created. The following types of charts are available: Line, Bar, Scatter, Heatgrid, Scorecard
9. Object tab — This pane shows databases and underneath schemas it lists → tables, views, stages, data pipelines, streams, and stored procedures.
10. Format query — This changes the SQL query format and displays it in a structured manner.
11. In the Results pane, you can sort the columns and also change the display format of the column. The below screenshot shows three display format options for the date column.
12. Keyboard shortcuts —The screenshot below is showing keyboard shortcuts for Snowsight.
13. Search in Results pane — You can search in the query result.
14. In Snowsight, when you execute a query it highlights the query in execution and also highlights the query compilation error.
Dashboards
Snowsight supports dashboard creation using new or existing worksheets. Dashboards are displays of one or more charts that can be rearranged.
Dashboards can only include worksheets you own; they cannot include shared worksheets.
The screenshot below shows dashboards created for Citibike data used in this blog post.
Closing Thoughts
Snowsight is available for the Snowflake services running in Microsoft Azure and AWS at present with a release on GCP in the pipeline.
Snowsight provides many exciting features for analysts, data engineers, and business users. SQL autocomplete and custom filters make it easier and faster to write queries; automatic contextual statistics give a better sense of the data, while collaboration capabilities make sharing seamless. Charts and dashboards make it easier to explore and share data across your organization. All of these features really help improve the overall productivity of users.
Although Snowsight is in preview, it is worth checking out. I hope this helps you to get started with Snowsight!
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Mohini Kalamkar is a Cloud and Data Engineering Consultant with Hashmap, an NTT DATA Company, providing Data, Cloud, IoT, and AI/ML solutions and consulting expertise across industries with a group of innovative technologists and domain experts accelerating high-value business outcomes for our customers.
