❄ Snowflake Data Matching Wizard

Connect directly to your Snowflake data warehouse and find matching clusters — no file exports needed

The Snowflake Data Matching Wizard is a browser-based, step-by-step tool that connects directly to your Snowflake data warehouse and uses Interzoid's AI-powered similarity algorithms to identify and cluster matching records within your tables. Whether you need to deduplicate company names, match individual names, or find address variations, the wizard walks you through the entire process — from connecting to Snowflake through selecting tables and columns to generating a downloadable match report.

The wizard supports 17 languages and guides you through a cascading connection flow: enter your Snowflake credentials, then select from your available warehouses, databases, schemas, and tables using dropdown menus populated directly from your Snowflake account. No need to manually look up or type database object names.

1Prerequisites

Before using the Snowflake Data Matching Wizard, you will need:

An Interzoid API Key: Register for an account and obtain your unique API license key. This key authenticates your requests and tracks usage credits.
A Snowflake Account: You will need a Snowflake account identifier (e.g. xy12345.us-west-2), a username, and a password with access to the tables you want to match against.
Available Credits: Each record processed consumes one API credit. Ensure your account has sufficient credits for the number of records in your table.

2Launch the Wizard and Enter Your API Key

Open the Snowflake Data Matching Wizard in your browser. Before beginning, enter your Interzoid API key in the top-right area of the header bar. Your key will be saved in your browser for future sessions.

API Key Field: Type or paste your API key into the input field in the header. Click the lock/eye icon to toggle visibility.
Check Credits: Click the Credits button to verify your current credit balance before starting a job.
Language Selection: Click the language dropdown in the navigation bar to switch between any of the 17 supported languages. The entire wizard interface will update immediately. You can also set the language via URL parameter: ?lang=fr for French, ?lang=ja for Japanese, etc.

Once your API key is entered, click Get Started on the introduction screen to begin the wizard.

Launch the Snowflake Data Matching Wizard

3Select a Matching Function

The wizard presents six matching functions. Choose the one that matches your data and use case. Each function card shows a description and the column parameters it requires.

Single-Column Functions

These functions analyze one column of data to find matches:

Function	Use Case	Column Required
Company Name Matching	Match variations like "IBM", "I.B.M. Corp", "International Business Machines"	Company Name
Individual Name Matching	Match "James Johnston", "Jim Johnston", "J. Johnston" as the same person	Full Name
Street Address Matching	Match "400 E Broadway St" with "400 East Broadway Street"	Address

Combination Functions

These functions use two columns together for higher matching precision:

Function	Use Case	Columns Required
Company + Address	Higher precision matching using both company name and street address	Company Name, Address
Company + Full Name	Contact deduplication using company and individual name	Company Name, Full Name
Address + Full Name	Person-at-address matching using address and individual name	Address, Full Name

Click on the card for your chosen function, then click Next to proceed.

4Connect to Snowflake

Enter your Snowflake connection credentials and use the cascading dropdown menus to navigate to your data. The wizard connects to Snowflake in real time and presents the available objects at each level.

Connection Flow

Credentials → Warehouse → Database → Schema

Account Identifier: Enter your Snowflake account identifier (e.g. xy12345.us-west-2). This is the same value you use to log into Snowsight or connect via SnowSQL.
Username & Password: Enter the credentials for your Snowflake user account. The wizard uses these to authenticate and discover available resources.
Connect Button: Click Connect to validate your credentials. If the connection succeeds, the wizard loads your available warehouses into a dropdown menu. If it fails, an error message will indicate what went wrong.
Warehouse: Select your compute warehouse from the dropdown. This is required for Snowflake to execute any queries. Once selected, the wizard automatically loads the list of available databases.
Database: Select the database containing the table you want to match against. The wizard then loads the available schemas within that database.
Schema: Select the schema (e.g. PUBLIC) that contains your target table.

Tip: Your Snowflake account identifier and username are saved in your browser for convenience. If you need to connect to a different Snowflake account, click Disconnect to reset the connection and enter new credentials.

Security Note: Your Snowflake password is never stored in the browser. It is sent directly to the matching API over HTTPS for each connection and discovery request and is not retained after the session ends.

Once you have selected a warehouse, database, and schema, click Next to proceed to table and column selection.

5Select Table, Columns, and Options

Choose the table to match against and configure which columns to use for matching and which columns to include in the output.

Table Selection

The wizard presents a dropdown of all tables available in the schema you selected. Choose the table containing the records you want to match. Once selected, the wizard loads the column names from that table.

Match Columns

For each matching parameter required by your chosen function, select the corresponding column from the dropdown. For example, if you chose "Company Name Matching," select the column that contains company names.

Single-column functions: Select one column for the matching parameter.
Combination functions: Select two different columns — one for each parameter. The two columns must be different.

Output Columns

Use the checkboxes to select which columns from the table you want to include in the match report output. At least one column must be selected. The match columns are automatically included even if you don't check them separately — this ensures the data you matched on always appears in the results.

Tip: Select additional identifying columns (like ID, city, state, etc.) to make the match report more useful for downstream analysis. You don't need to include every column — just the ones that help you identify and act on the matches.

Output Options

Show Similarity Keys: When enabled (default), each output record includes the generated similarity key as the last column. Records with the same key are matches. Disable this if you want clean output with only the selected data columns.
Matches Only: When enabled (default), only records that have at least one other matching record are shown. Disable this to see every record in the table after processing, sorted by similarity key.

Click Next when your selections and options are configured.

6Review and Run

The final screen shows a summary of all your selections: matching function, Snowflake account, warehouse, database, schema, table, column assignments, and output options. Review these carefully before proceeding.

Click the green Run Match button to start processing. The wizard will:

Validate your API key and check that your account has sufficient credits for the job.
Connect to Snowflake and read the selected columns from your table.
Process each record through the selected matching algorithm using concurrent workers for performance.
Generate the match report with records sorted and grouped into clusters of matching entries.

A progress indicator is shown while the job runs. Processing time depends on the number of records — most tables complete within seconds, while very large tables (up to 500,000 records) may take a minute or more.

Note: If the matching engine encounters too many errors, the job will stop early and display an error message. Verify that your Snowflake connection is still active and that the selected table and columns are accessible.

7Interpret the Results

The match report appears in the results panel at the bottom of the screen. Records are organized into clusters — groups of records that the AI has determined to be matches. Each cluster is separated by a blank line for readability.

Example Output

For a company name match on a Snowflake table with columns COMPANY, ADDRESS, CITY, STATE and similarity keys enabled:

IBM Corporation,1 New Orchard Rd,Armonk,NY,d477E1d7sG6dja3hDNsk9P
I.B.M. Corp,1 New Orchard Road,Armonk,NY,d477E1d7sG6dja3hDNsk9P

Microsoft Inc.,1 Microsoft Way,Redmond,WA,k8Rp2mNx4wQjL9vB3cYh7T
Microsoft Corporation,One Microsoft Way,Redmond,WA,k8Rp2mNx4wQjL9vB3cYh7T
MSFT Corp,1 Microsoft Way,Redmond,WA,k8Rp2mNx4wQjL9vB3cYh7T

In this example, the first cluster contains two records identified as variations of IBM, and the second cluster contains three records identified as variations of Microsoft. The last column in each row is the similarity key — all records sharing the same key are considered matches.

8Save Your Results

Click the Save Results button above the results panel to download the match report as a CSV file. On supported browsers, a save dialog will appear allowing you to choose the file name and location. On other browsers, the file will download automatically.

The saved file is clean, delimited text that can be imported directly into spreadsheets, databases, or other data processing tools for further analysis.

Data Pipeline Integration: The match report output has no metadata or headers — just data rows and blank-line cluster separators. This makes it suitable for direct use in automated data pipelines. You can also call the underlying REST API directly for fully automated Snowflake matching workflows.

9API Access for Developers

The Snowflake Data Matching Wizard is powered by a REST API that can also be called directly from your own applications, scripts, or data pipelines. This allows you to automate Snowflake-based matching jobs without using the browser wizard.

Example API Call

$ curl "https://match.interzoid.com/match?\
driver=snowflake&\
db_host=xy12345.us-west-2&\
db_user=MY_USER&\
db_password=MY_PASSWORD&\
db_database=MY_DB&\
db_schema=PUBLIC&\
db_warehouse=COMPUTE_WH&\
table=CUSTOMERS&\
columns=COMPANY,ADDRESS,CITY,STATE&\
function=company-name-only&\
company_column_name=COMPANY&\
apikey=YOUR_API_KEY&\
showkeys=true&\
matchesonly=true"

Snowflake Match API Parameters

Parameter	Required	Description
`driver`	Yes	Set to `snowflake`
`db_host`	Yes	Snowflake account identifier (e.g. `xy12345.us-west-2`)
`db_user`	Yes	Snowflake username
`db_password`	Yes	Snowflake password
`db_warehouse`	Yes	Snowflake compute warehouse name
`db_database`	Yes	Snowflake database name
`db_schema`	Yes	Snowflake schema name (e.g. `PUBLIC`)
`table`	Yes	Name of the table or view to read from
`columns`	Yes	Comma-separated list of column names to include in the output
`function`	Yes	One of: `company-name-only`, `fullname-only`, `address-only`, `company-and-address`, `company-and-fullname`, `address-and-fullname`
`apikey`	Yes	Your Interzoid API license key
`company_column_name`	When applicable	Name of the column containing company names
`fullname_column_name`	When applicable	Name of the column containing individual names
`address_column_name`	When applicable	Name of the column containing street addresses
`showkeys`	No	`true` (default) or `false` — append similarity key to output
`matchesonly`	No	`true` (default) or `false` — show only matching clusters

Discovery API

The wizard's cascading dropdown menus are powered by a /discover endpoint that you can also call directly to enumerate Snowflake resources:

# List warehouses (also validates credentials)
$ curl "https://match.interzoid.com/discover?db_host=xy12345.us-west-2&db_user=MY_USER&db_password=MY_PASSWORD&resource=warehouses"

# List databases within a warehouse
$ curl "https://match.interzoid.com/discover?...&db_warehouse=COMPUTE_WH&resource=databases"

# List schemas within a database
$ curl "https://match.interzoid.com/discover?...&db_warehouse=COMPUTE_WH&db_database=MY_DB&resource=schemas"

# List tables within a schema
$ curl "https://match.interzoid.com/discover?...&db_database=MY_DB&db_schema=PUBLIC&resource=tables"

# List columns within a table
$ curl "https://match.interzoid.com/discover?...&db_schema=PUBLIC&table=CUSTOMERS&resource=columns"

Each discovery call returns a JSON response with the list of available resource names:

{"resource":"warehouses","items":["COMPUTE_WH","ANALYTICS_WH"]}

The API returns plain text output identical to what the wizard displays, making it suitable for piping into other tools or storing directly as a file.

View All Interzoid APIs Getting Started Guide CSV/TSV Matching Wizard Docs

The Snowflake Data Matching Wizard makes it easy to discover hidden duplicates and matching records directly within your Snowflake data warehouse. Whether you use it interactively through the browser-based wizard or programmatically through the API, it delivers clean, actionable match reports that help you improve the quality, consistency, and value of your data assets — without ever exporting a file. If you have any questions or need assistance, don't hesitate to reach out to our support team.