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How to Prepare and Explore Data with KNIME and Snowflake (ELT)

<p><strong>How to Prepare and Explore Data with KNIME and Snowflake (ELT)</strong><br><br>This workflow is an example of how to read different customer data files in KNIME and upload it to Snowflake. Once uploaded the data is transformed and analysed within Snowflake and the result is visualized in KNIME.</p>

URL: KNIME Snowflake Extension Guide https://docs.knime.com/latest/snowflake_extension_guide/index.html

How to Prepare and Explore Data with KNIME and Snowflake (ELT)

This workflow is an example of how to read different customer data files in KNIME and upload it to Snowflake. Once uploaded the data is transformed and analysed within Snowflake and the result is visualized in KNIME.

📍Technical Note:

If you don't have a Snowflake account, you can sign up for a free 30-day trial account (when signing up, select Enterprise edition and choose any Snowflake cloud/region - preferably AWS or Azure).

Configure the Snowflake Connector node:

After signing up, navigate to your Snowflake Account details. There, you'll find key information to configure the node:

  • Account identifier (input it in Full account name field)

  • Login name (input it in Authentication > Username & password field). The password field is the password used to log in to your Snowflake account.

  • Role (input it in Default access control role). If you're using a free trial account, make sure the role is ACCOUNTADMIN. Otherwise, input the role that is enabled for your account (your role should have write permissions).

  • Stay in your Account details and navigate to the Config File tab. Select the warehouse you prefer (e.g., SNOWFLAKE_LEARNING_WH, if you're using a free trial account) and input the warehouse name in the Virtual warehouse field.

📍Technical Note:

[For users with a free 30-day trial account] In the DB Table Structure Creator and DB Row Inserter nodes, keep the default configurations and simply execute the nodes.

[For users with a regular account] In the DB Table Structure Creator and DB Row Inserter nodes, click on the Browse button and select your preferred Database and Schema names (they must already exist). Make sure the Table name stays as per default configuration.

4. Exploring

Visualize the aggregation result in KNIME

3. Transformation

Transformation are done using the processing power of Snowflake

2. Loading

The extracted data is uploaded into two new tables in Snowflake

1. Extraction

Extract data from Excel and CSV files

Create callstable
DB Table Structure Creator
DB Connection Closer
Connect todatabase
Snowflake Connector
Inner Join 2 tables based on customer Phone
DB Joiner
Insert rows
DB Row Inserter
Insert rows
DB Row Inserter
Create contractstable
DB Table Structure Creator
Contract data
CSV Reader
Calls data
Excel Reader
Show aggregationresult
Bar Chart
Aggregate by area code and churn
DB GroupBy
Convert churn to nominal
DB Query
Read aggregated data into KNIME table
DB Reader

Nodes

Extensions

Links

Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: rosy
Created at: 2015-04-23
On NodePit since: 2026-03-20
Last update: 2026-03-20
Created with KNIME version: v5.11.0
Tags: SnowflakeELTCustomer IntelligenceMarketing AnalyticsDBDatabase

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