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High-Performance Snowflake Data Matching

Identify inconsistent, matching, and duplicate data across your Snowflake tables in just a few clicks.

A guided, read-only analysis tool that turns better data quality into better Snowflake ROI.

Launch the Matching Wizard Read the Documentation
Built for Snowflake

Better Data. Better Snowflake ROI.

The Snowflake Matching Wizard connects directly to your Snowflake data tables in read-only analysis mode. In a guided, step-by-step flow, you'll generate AI-enhanced match reports that surface inconsistent values, redundant records, and duplicate entries across any number of Snowflake data assets. Parallel processing delivers maximum performance, even on large tables.

Open snow-match.interzoid.com

See It in Action

A quick look at the Matching Wizard experience, from connecting to Snowflake through reviewing your match report.

Choose Matching Type

Choose Matching Type

Select the type of matching you want to perform: company names, individuals, addresses, and more.

Connect to Snowflake

Connect to Snowflake

Securely connect to your Snowflake account in read-only mode.

Select Tables and Columns

Select Tables and Columns

Choose the Snowflake tables and columns containing the data you want to analyze.

Run and Review Results

Run and Review Results

Run the job and review your match report, with clusters of matching, duplicate, and inconsistent records.

Why Teams Use the Matching Wizard

Effortless to Use

A guided wizard walks you through connecting to Snowflake, choosing your data, and generating a match report. No SQL or scripting required.

Read-Only and Safe

The wizard operates entirely in read-only analysis mode. Your Snowflake data is never modified, making it safe to run against any of your tables.

AI-Enhanced Matching

Advanced AI-enhanced similarity algorithms cluster matching records and reveal duplicates and inconsistencies that exact-match queries miss entirely.

Better Snowflake ROI

Cleaner data means more reliable analytics, better customer insights, and fewer wasted compute cycles processing redundant records.

Parallel Processing for Maximum Performance

A multi-threaded, distributed cloud architecture processes large Snowflake tables in parallel, delivering match reports fast, even at high data volumes.

Actionable Match Reports

Receive clear, organized reports that highlight clusters of similar records, ready to drive deduplication and consolidation decisions.

How It Works

From connection to match report in three simple steps.

1

Connect to Snowflake

Connect directly to your Snowflake database. Snowflake Reader Accounts are fully supported and recommended for read-only access.

2

Select Tables and Columns

Choose the Snowflake tables and columns containing the data you want to analyze for matches, duplicates, and inconsistencies.

3

Run and Review Results

Run the matching job and review a clear, AI-enhanced report identifying clusters of matching, duplicate, and inconsistent records.

Resources

Everything you need to get started, from a sample report to a step-by-step video walkthrough.

Sample Match Report

See an example match report for company name data, showing how matching clusters are presented.

View Sample Report

Documentation

Read the complete documentation covering setup, connection, and matching options.

Read the Docs

Video Tutorial

Watch a step-by-step YouTube walkthrough of the Snowflake Matching Wizard from start to finish.

Watch on YouTube

Works With Every Snowflake Deployment

The wizard connects with standard Snowflake credentials, so it reads from any account on any cloud, in any region, on any edition.

Snowflake on AWS
Snowflake on Azure
Snowflake on Google Cloud
Any Snowflake Region
All Snowflake Editions Standard through Business Critical
Reader Accounts Share only what you choose
Any Warehouse Size X-Small through the largest
Tables and Views Including secure views
Shared Databases Data shared in to your account

No connector to install, no integration to deploy, and nothing running inside your Snowflake account. Point the wizard at a warehouse, database, schema, and table, and it reads only the columns you select.

What You Can Match

Four data types, plus combinations that raise precision when one field alone is too broad

Organization Names

Resolve Acme Corp, ACME Corporation, and Acme Inc. to a single organization, across the legal suffixes, punctuation, abbreviations, and spelling variations that make company names so inconsistent.

Individual Names

Match James Johnston, Jim Johnston, and J. Johnston as the same person, handling nicknames, initials, middle names, and name ordering.

Street Addresses

Reconcile 400 E Broadway St with 400 East Broadway Street, resolving directional abbreviations, street type variations, unit designations, and spacing.

General Text

Generate similarity keys for other text values, so product names, descriptions, and free-form fields cluster the same way that names and addresses do.

Combination Matching

Require two fields to agree at once: organization with address, organization with individual name, or address with individual name. This separates the Dallas branch from the Phoenix branch while still recognizing that both spell the parent company four different ways.

Similarity Keys and Clusters

Every value receives a key representing the entity behind the text rather than the characters themselves. Records sharing a key are grouped into clusters, which makes each match auditable instead of something to take on faith.

Frequently Asked Questions

Which Snowflake deployments are supported?

All of them. Snowflake accounts hosted on AWS, Azure, or Google Cloud are supported in any region, across every Snowflake edition, using any warehouse size. Tables, views, and shared databases can all be matched, and Reader Accounts are supported for sharing only the data you choose.

Does Interzoid modify my Snowflake data?

No. Processing issues SELECT statements against the table and columns you choose and nothing else. Nothing is written, updated, or deleted, and no schema objects are created. Results are returned to your browser, and you decide what to do with them.

Do I need to export my data first?

No. Interzoid connects directly to your Snowflake account and reads the columns you select. There is no CSV export, no staging area, and no copy of your data to secure, track, or delete afterward.

How are my Snowflake credentials handled?

Credentials are transmitted over HTTPS with each request and are not retained after the session ends. Because processing is read-only, the recommended practice is to use a Snowflake Reader Account or a dedicated read-only role, either of which can be revoked at any time.

How is usage measured?

Each record processed consumes one Interzoid API credit. Trial credits are included with a new API account, so a first table can be matched at no cost, and high volume tables are supported for production workloads.

Can I run this from my own applications instead of the browser?

Yes. The same processing is available as a REST API that can be called from scripts, applications, and data pipelines, which allows Snowflake matching jobs to be automated without using the browser wizard.

Ready to See What's Hiding in Your Snowflake Data?

Generate your first match report in minutes. No installation, no code, no changes to your data.

Launch the Matching Wizard Read Documentation

Questions? Contact our team at support@interzoid.com