Data Warehouse connector

The Snowflake data catalog your whole team can trust.

The Dawiso Snowflake connector turns your account into a searchable data catalog: every database, schema, table and column, with lineage to every BI report downstream.

Read the docs

Live connector Stable connector

Snowflake

Dawiso

Metadata-only · your data never leaves the source

Type: Cloud data platform
Auth: Key-pair authentication (RSA)
Sync: Scheduled, incremental
Direction: Read-only · metadata

First things first

What is a data connector?

Metadata-only Read-only access Incremental sync Cross-system lineage

A data connector is the bridge between a tool in your stack and the catalog that gives you a unified view of it. Once a connector is configured, it reaches into the source system on a schedule, reads out the metadata - schemas, tables, dashboards, jobs, ownership, lineage - and represents it inside the catalog. Your actual rows and values stay where they are.

Connectors are the reason a data catalog can answer questions like "which Power BI dashboard depends on this Snowflake table?" or "who owns the orders topic in Kafka?" - automatically, without anyone keeping a spreadsheet up to date.

Three properties separate a good connector from a brittle one: it should be read-only and safe, it should be incremental so a full re-scan isn't required for every refresh, and it should resolve lineage across system boundaries, not just inside one tool.

About the platform

What is Snowflake?

Snowflake is the cloud data platform built on separated storage and compute. Data teams at banks, retailers and manufacturers use it as their analytical home base: warehousing, secure data sharing with partners, and the foundation for everything from finance reporting to ML features.

Snowflake Horizon Catalog covers what lives inside Snowflake. The hard part is what doesn't: the Power BI report consuming the table, the data product the business actually uses, the policy security signed off on. That's where the Dawiso Snowflake data catalog joins the picture: read-only, metadata-only, and cross-platform.

Architecture

How Dawiso connects to Snowflake

A small read-only role on the Snowflake side. The Dawiso scanner pulls metadata on a schedule. Everything ends up in your catalog, business-readable.

Source

Snowflake account

Databases & schemas
Tables, views, dynamic tables
Pipes, streams, tasks
Functions & procedures

REST · JDBC

Dawiso scanner

Read-only metadata

Schema & object discovery
Dependency resolution
SQL flow parsing (optional)
Sampling on opt-in

Internal

Catalog

Dawiso platform

Searchable metadata
Lineage & ownership
Business glossary
Policy & classifications

Connection details

Protocol: Snowflake JDBC + INFORMATION_SCHEMA and ACCOUNT_USAGE views
Authentication: Key-pair (RSA) · dedicated read-only role
Lineage: Object dependencies resolved from SNOWFLAKE.ACCOUNT_USAGE; object-level lineage built from parsed view and procedure SQL via Data Flow parsing on enterprise plans

Setup

Connect Snowflake in 4 steps

01

Create a read-only role

Create DAWISO_INTEGRATION_ROLE with USAGE on the warehouse and database, REFERENCES on tables and views, MONITOR on pipes and tasks. Add FUTURE grants so new objects scan automatically.
02

Set up key-pair auth

Generate an RSA key pair with openssl, assign the public key to the integration user. Compatible with Snowflake's November 2025 password phase-out.
03

Connect and pick databases

Add the account host, warehouse, role and encrypted private key in Dawiso. Choose which databases to ingest in one comma-separated list.
04

Run ingestion

Scheduled incremental sync keeps the catalog current. Flow parsing resolves object-level lineage on enterprise plans.

Capabilities

What you get with the Snowflake connector

Schema & table catalog

Every database, schema, table and view is searchable, with column descriptions, types and tags.
Object-level lineage

Cross-platform lineage from a Power BI visual through Snowflake views down to the raw ingest table, via Data Flow parsing on enterprise plans.
Business glossary alignment

Tie Snowflake tables and columns to glossary terms so business users get the same definition as the BI report and the data product.
PII classification

Classify a column once. Dawiso flags every Snowflake column carrying email, IBAN or government IDs across all databases.
Usage & cost insight

ACCOUNT_USAGE surfaces query frequency and credits per table, so 'which assets are worth keeping warm' is finally a measurable question.
Ownership & certification

Mark tables as certified, deprecated or under review. The owner is visible directly in the catalog and on the Snowflake side.

Business value

Why teams turn on the Snowflake connector

-65%
Fewer 'which table?' pings

Analysts find the certified gold table in Dawiso instead of pinging the data team to ask which silver table maps to revenue.
10x
Faster impact analysis

Before altering a Snowflake column, see exactly which views, BI reports and ML features depend on it. Seconds, not days.
Audit-ready
GDPR & DORA evidence

Sensitive columns are classified once and the policy follows them through views, joins and downstream BI, with a full audit trail.

Ready to catalog your Snowflake?

Set up the connector in an afternoon. See your first lineage graph the same day.

Read the docs

Frequently asked questions

Still curious? Talk to our team ->

Does Snowflake have a data catalog?

Snowflake ships Horizon Catalog for objects inside Snowflake. Dawiso adds the cross-platform layer Horizon does not cover: BI reports, business glossary and policies, with object-level lineage that spans all of them.

What is the difference between Snowflake Horizon Catalog and open catalog?

Horizon governs data inside Snowflake; Polaris (open catalog) is an open-source Iceberg catalog. Dawiso is different again - a cross-platform business catalog that reads Snowflake metadata read-only and connects it to your whole stack with lineage and a glossary.

What is metadata in Snowflake?

Snowflake metadata lives in INFORMATION_SCHEMA and ACCOUNT_USAGE - databases, schemas, tables, columns, usage and access history. Dawiso reads it read-only and turns it into a searchable catalog with lineage, ownership and classification.

What permissions does Dawiso need in Snowflake?

A dedicated read-only role (DAWISO_INTEGRATION_ROLE) with USAGE and REFERENCES grants on objects, plus the SNOWFLAKE.OBJECT_VIEWER database role for dependency resolution. Dawiso never modifies your data.

Does Dawiso copy our Snowflake data?

No. Dawiso queries INFORMATION_SCHEMA and ACCOUNT_USAGE views for metadata only. Row-level data stays inside Snowflake. Column profiling and sampling are opt-in per data source.

How is lineage built?

Object dependencies come from SNOWFLAKE.ACCOUNT_USAGE. For object-level resolution, Dawiso parses SQL from view and stored-procedure definitions. Flow parsing is available on enterprise plans.

Does the November 2025 password phase-out affect Dawiso?

No. Dawiso supports Snowflake key-pair authentication today: generate an RSA key, assign the public key to the integration user, supply the encrypted private key and passphrase when creating the connection.