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Snowflake delivery

Snowflake real estate data: querying Canadian property intelligence without the pipeline

The most valuable real estate dataset in Canada is the one that lives inside your own Snowflake account and updates itself every week. That is not a metaphor — it is how Snowflake Secure Data Share works, and it is why enterprise data teams are moving away from SFTP drops and custom ETL pipelines for property data.

The zero-ETL data model

Traditional real estate data delivery looks like this: a vendor drops a file on an SFTP server every week, a pipeline picks it up, validates the schema, loads it into staging, runs transformations, and publishes to production. When the schema drifts, the pipeline breaks. When the refresh is late, downstream dashboards go stale. When a new field is added, three teams have work to do.

Snowflake Secure Data Share eliminates that entire chain. The provider mounts their dataset into the consumer's Snowflake account as a read-only database. No file transfer. No ingestion. No transformation. Queries run directly against the provider's tables, inside the consumer's own compute environment.

Snowflake Secure Data Share is not file delivery over a network. It is a live reference into the provider's dataset, queryable from the consumer's account with no data movement.

What changes operationally

For the data engineering team, Snowflake delivery changes the operational model in five ways:

What BrightCat delivers on Snowflake Marketplace

BrightCat publishes five distinct listings on Snowflake Marketplace, each covering a specific product line:

Each listing provides a sample schema for evaluation. Once a commercial agreement is in place, the consumer receives access to the full production schema under the same delivery mechanism.

How queries actually look

A typical enterprise query against BrightCat's Snowflake data looks like standard SQL:

Join the consumer's customer address table against BrightCat Listings by postal code. Filter for properties with a status of NEW in the last week. Enrich with property characteristics from BrightCat Core. Export the result to the consumer's CRM for an acquisition workflow.

No file transfer happens. No pipeline runs. The query executes in the consumer's Snowflake warehouse against tables that are mounted from BrightCat's environment. The result lands in the consumer's result set, ready for the next step.

Geography and regions

Snowflake data shares are region-specific. BrightCat's primary data share is hosted in Azure Canada Central, which is the most common region for Canadian enterprise consumers. Cross-region access is supported through Snowflake's cross-region replication for consumers in other regions.

For teams not on Snowflake

Not every enterprise data team runs on Snowflake. For teams on Databricks, BigQuery, or traditional on-prem warehouses, BrightCat supports flat file delivery (Parquet or CSV) and the MCP connector for AI and agent workflows. The underlying dataset is identical; only the delivery mode differs.

Frequently asked questions

How is BrightCat data accessed on Snowflake?
Through Snowflake Marketplace, as a Secure Data Share. The dataset mounts into the consumer's Snowflake account as a read-only database. No file transfer, no ingestion, no pipeline.
What is the refresh cadence?
Weekly. When BrightCat updates the source, the change is immediately visible to every consumer querying the share.
Which Snowflake region is BrightCat hosted in?
Azure Canada Central is the primary region. Cross-region access is available through Snowflake's replication mechanism for consumers in other regions.
Is there a sample dataset for evaluation?
Yes. Every Marketplace listing includes a sample schema that consumers can query before entering a commercial agreement. Request access to evaluate.
How does billing work?
Query compute runs on the consumer's Snowflake account, which means the consumer pays for their own compute. The data licence is priced separately through the commercial agreement.
What if my team isn't on Snowflake?
BrightCat supports flat file delivery (Parquet or CSV) and the MCP connector for AI-native workflows. The data is the same; only the delivery mode differs.
The right way to deliver real estate data to an enterprise is to stop delivering it. Mount the dataset, refresh it at the source, and let the consumer query it where their work already lives.
BrightCat on Snowflake Marketplace · Azure Canada Central · Updated weekly

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