We all know that Snowflake has been tremendously dominating the space of modern data warehouse for the past few months. Being the only data warehouse built for the cloud, Snowflake has been reducing the expenditure of its clients by 10x times with its powerful multi-cluster hybrid architecture and by leveraging all advantages of the cloud.

Now, stepping into Q3 2020, Snowflake has released a bunch of new features that are interesting and some being the need of the hour. This blog will brief on Snowflake’s upcoming features and new enhancements.

Snowsight

Snowsight is the advanced version of the regular SQL worksheet in Snowflake which is specifically designed for data analysis. They are available in a completely new web interface and are re-designed to include features like Schema browser, faster query writing and interactive query result features.

1. Worksheets

With the existing Worksheets, we can export our Worksheet as .sql files to a local directory or import .sql files into Worksheets. With this update, we can save the Worksheets into folders or separate files categorically thereby giving Worksheets a more organized structure which helps us to retrieve them faster and search logically.

With these Worksheets, we can assign the values to session context for Role, Warehouse and Database. Running the SQL query will return the data and appropriate visualization, which can later be modified by the user to dive deep into the data. This Worksheet also has a list of shortcuts that can be utilized as quick controls.

2. Schema Browser

With this feature, we can search directly across databases and schemas with a keyword belonging to a column, table, or view.

Another unique thing about this feature is, we can compare various tables with their structures in a single-window along with their data types. A quick preview of the data is also available with this schema browser as depicted in the below screenshot.

3. Faster Query Writing

Smart Autocomplete: This feature helps us to query faster as it suggests the keywords for completion. This Smart Autocomplete identifies all the columns, tables, and views within a schema.

4. Data Filters

These are reusable code snippets that hold a list of values or a subquery. During querying we can have this template and use wherever applicable (say we want to filter certain Accounts – 1000041, 1000099, 1000231, 1000312. We can create a custom filter with these and reuse wherever applicable in our query).

Quick access to reference details: This feature enables us to view a short description of the syntax of the function we are trying to use. We can also navigate to the Docs with the hyperlink provided to get more information regarding the same.

5. Interactive Query Results

Rather than just showing the results in a table format, Snowflake has come up with a data profiling feature that helps us to statistically analyze the data much better.

6. Data Profiling

With every query being executed, Data profiling creates an automated contextual statistic for all columns as highlighted in the below picture. We can also pick a column, cell, or range in the result to view more information on it. A Histogram is also generated by default in the inspector pane for the date, time, and numeric columns.

As an extension of this blog, we have the next blog ‘Snowflake – Sneak Peek of its Upcoming Features Part 2’ which will concentrate mainly on Attractive Data Visualizations, Sharing, and Collaboration features.

Learn more about Visual BI Solutions Snowflake offerings here and read more about similar Self Service BI topics here.