Jourier builds the Google DV 360 integration into your Snowflake environment. Google DV 360 data flows in via real-time CDC and webhooks, lands as modeled tables in Snowflake, and becomes the layer that BI tools, AI agents, MCP servers, and bespoke applications all read from.

You keep using Snowflake for what it's good at (storage, compute, governance) and Jourier brings the modeling, the pipelines, and the consumption layers on top. Multi-touch attribution, campaign ROAS reporting, and cross-channel performance delivered through a real engineered application your team owns.

Campaign data from Google DV 360 arrives at the cadence the platform reports it — sometimes hourly, sometimes daily, sometimes on a 24-hour delay. Jourier's pipeline tracks each source's freshness explicitly so dashboards label numbers by how recent they actually are.

Time-travel and zero-copy clones in Snowflake make Google DV 360 data safer to experiment with — analysts can branch a copy, test transformations, and merge back without affecting production. Jourier wires this into the engagement workflow so model changes ship as PR reviews rather than as direct production edits.

Result: Google DV 360 data lives in Snowflake as engineered tables, ready for multi-touch attribution and for whatever consumer layer reads from Snowflake next — BI, AI agents, MCP servers, custom applications.

Pick Snowflake as your Google DV 360 backend when your customer cloud already hosts it, or when the workload pattern fits Snowflake's strengths. Jourier doesn't sell Snowflake compute. Your contract stays with Snowflake. We bring the engineering and the modeling on top, plus the consumption layers (BI, AI agents, MCP, bespoke apps) that read from Google DV 360 once it's in Snowflake.

Can I land Google DV 360 data in my Snowflake environment?

Yes. Jourier builds a bespoke Google DV 360 → Snowflake pipeline that lands data continuously in your existing Snowflake workspace. Real-time CDC where Google DV 360 supports it, scheduled polling and webhooks otherwise. Tables are modeled, documented, and ready for multi-touch attribution. The pipeline runs on Snowflake's native compute (no second platform to manage), and the modeling layer above it joins Google DV 360 with the rest of your operational systems.

Does Jourier require Snowflake, or can I use a different warehouse for Google DV 360?

Snowflake is one of several supported backends. If your stack already runs on Snowflake, Databricks, Microsoft Fabric, BigQuery, Postgres, Supabase, or Redshift, the Google DV 360 pipeline adapts to it. Pick Snowflake when it fits your team's skills, your customer cloud's hosting, and Google DV 360's data shape. Jourier doesn't push a specific warehouse — we evaluate the choice with you against existing contracts, compliance, and team familiarity.

How does the Google DV 360 model in Snowflake differ from off-the-shelf Snowflake content?

Off-the-shelf Snowflake content is generic — schemas designed for the average customer, not yours. Jourier's Data Hub on Snowflake is bespoke: modeled to your operations, joined across Google DV 360 and the rest of your operational systems, with the entity definitions your business actually uses. Same Snowflake engine underneath, but a layer designed for your business. The result is reports, applications, and AI tools that read the same numbers your team uses.

Who owns the Google DV 360 → Snowflake pipelines and schemas?

You do. Jourier delivers everything as code in your Snowflake workspace — pipeline definitions, modeled tables, data dictionaries, runbooks, access-control config. Hand it to another vendor or take it over yourself whenever you want. No vendor lock-in, no per-engagement licence. The Snowflake subscription stays directly with Snowflake; we don't add a markup.

Can I switch from Snowflake to a different warehouse later, keeping the Google DV 360 integration?

Yes. The Google DV 360 pipeline can re-target. Most of the SQL ports between Snowflake and another warehouse with light editing — sometimes just dialect changes, sometimes a partition-strategy refactor. Migrations of this kind are part of what Jourier does. The modeling layer (entities, joins, business rules) stays the same; only the underlying compute and storage move.

How long does landing Google DV 360 into Snowflake take?

First sync is typically instant to one day. A scoped engagement covering Google DV 360 plus the modeled tables for the workflows that matter (multi-touch attribution, campaign ROAS reporting) usually runs three to six weeks before production. Bigger transformations are phased. Jourier handles the Google DV 360 pipeline, the Snowflake schema design, the access controls, and the documentation. Your team validates the model and trains the analysts.

How predictable are Snowflake compute costs for this workload?

Predictable, with the right design. Jourier's modeling decisions affect Snowflake cost directly — partitioning, clustering, materialised views, query patterns. We design the Google DV 360 model on Snowflake for the access patterns your team actually has, not for theoretical generality. Most customers see Snowflake compute costs roughly proportional to user activity once steady-state is reached. We can co-design the schema with cost limits in mind if that's a constraint.

Can Google DV 360 be joined with other operational systems in Snowflake?

Yes — that's the point of the Data Hub. Once Google DV 360 is in Snowflake, the modeling layer joins it with CRM, ERP, billing, product analytics, and any other source you've integrated. Entity resolution (same customer / same product / same transaction across systems) is handled in the modeling layer. The result: a Snowflake dataset where a single 'customer' row reflects every system that knows about that customer, joined consistently.

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Aleksi Stenberg Founder & CEO