Skip to content

Quick Start

Follow these steps to quickly set up and start using your Analytics workspace for interactive Snowpark exploration.

1. Install Packages

Analytics uses a different python environment than the rest of the platform. To install the packages, open a terminal and navigate to the data_analytics folder:

cd packages/data_analytics/

Then install the packages by running:

uv sync
Install Packages

Install Packages

Best Practice

Deactivate your current shell before installing the packages by entering the deactivate command.

2. Connect to Snowflake

Example 
from analytics_utils.snowpark import session

Once your environment is ready, you can connect directly to Snowflake via Snowpark using the built-in session helper.

This automatically: - Loads your Snowflake credentials from .env - Connects to your assigned database, schema, role, and warehouse - Prints the current session info for confirmation

3. Query Methods

There are several methods that can be used to query data:

Dataframe API 
session.table("raw.public.customers")
SQL API 
session.sql("select * from raw.public.customers")
SQL Magic 
%%sql

select
    *
from raw.public.customers

All are equivalent and valid as they are compiled and run on the snowflake warehouse.

Query Methods

Query Methods

4. Using Display

Example 
from analytics_utils.snowpark import display

The display() function overrides the default jupyter notebook behavior with a powerful tool to explore the data. It is optimized to work with Snowpark dataframes and ensures a seamless experience for users.

Display Table

Display Table

5. Display Visualization

Beyond tabular display, display() also supports rich visualizations similar to Tableau — directly in your notebook. You can drag-and-drop fields to create charts, pivot tables, and explore trends.

Display Visualization

Display Visualization