Data warehouse implementation: one governed source of truth
What’s included
01- ✓Source connectors and ingestion
- ✓Modelled layers with tests
- ✓Data dictionary and lineage
- ✓Freshness and quality monitoring
- ✓Access control by role
- ✓Cost-aware warehouse sizing
The details
02Do you need a warehouse, or just a dashboard?
A warehouse earns its price when several systems — an ERP, a CRM, Tally, a store, a pile of spreadsheets — have to be combined, history has to be kept, and more than one team or tool reads from the result. It is the foundation that dashboards, reports and AI tools sit on, not a report in itself.
If you need one agreed set of management numbers from a few sources, the Business Intelligence Dashboard at ₹45,000 is the smaller step. If you are not yet sure why your systems disagree, the Drift Audit at ₹49,000, over 2–3 weeks, maps where records stop agreeing first. We diagnose. You get clarity. We quote only after that.
What does “governed” mean in practice?
Data arrives from each source through a connector. dbt then shapes it in layers — cleaned first, then combined into business-ready tables — and the layers carry tests that flag a broken rule, such as a duplicate invoice number or an order without a customer.
Tables and columns are described in a data dictionary, and lineage shows which source feeds which number. Freshness and quality monitoring flags a nightly load that is late or looks wrong, so it is caught by a check rather than noticed in a report. Access control by role keeps sensitive tables, such as payroll or patient records, visible only to the people who should see them.
What will the warehouse cost to run?
Snowflake bills separately for storage and for the compute that loads and queries use, and those bills are not part of this price. A warehouse sized carelessly keeps costing money every month, which is why cost-aware sizing is in the package: the warehouse is sized to your actual loads and query patterns, and we walk through what that means for your volumes on the scope call.
The infrastructure is written in Terraform, so the set-up is code that can be reviewed, repeated and changed deliberately, rather than a series of console clicks nobody remembers. That matters the first time someone has to rebuild an environment or check what changed and when.
How long does it take, and what is not included?
Delivery is 3 months or more; the exact length is set in the proposal once the sources in scope are known, and your fixed price arrives in writing after the scope call. As on every engagement, you work directly with the founder, on a shared board, with a working demo on day one, so the warehouse is visible long before it is finished.
Not included: Snowflake’s own bills, fixes inside your source systems, and one-off moves out of a system you are retiring, which is Data Migration & Quality at ₹15,000. Dashboards on top are their own packages: the Business Intelligence Dashboard at ₹45,000 or Sales & Revenue Analytics at ₹40,000.
How it works
03- 0115-min callTell us what’s breaking. We ask the questions that change the price.
- 02Scope in writingA fixed quote and a written scope: what’s in, what isn’t.
- 03Build & reviewWorking software early, with review rounds on real screens.
- 04LaunchWe go live with you, train your team and hand over access.
- 05SupportFixes, changes and growth on a retainer, if you want one.
FAQ
04What does a data warehouse implementation cost?
The Data Pipeline & Warehouse package starts at ₹1,75,000 and takes 3 months or more. Snowflake bills its storage and compute separately. Your fixed price arrives in writing after a 15-minute scope call, with the sources in scope listed one by one in the proposal.
How fresh will the data be?
The warehouse is refreshed nightly, so each morning’s reports reflect the previous day. A source that needs refreshing more often than nightly is a scoping question: bring it to the call, and the proposal will say what was agreed for it.
Which of our systems can it connect?
Source connectors and ingestion are part of the package, and the list of sources is agreed with you. Each system you name — an ERP, a CRM, TallyPrime, an online store, spreadsheets — is assessed on the scope call, and the proposal lists exactly which ones are connected.
Why Snowflake, dbt and Terraform?
Snowflake stores the data and runs the queries, dbt turns raw tables into tested and documented models, and Terraform defines the infrastructure as code. Together they make the warehouse checkable: you can see what each number is built from and what changed. The proposal names the stack, so any existing platform you run is discussed before it is written.
Who looks after it once it is live?
The data dictionary, lineage and monitoring are there so your own team can see what broke and where. If you would rather keep us involved, Managed Support & Growth starts at ₹14,000 and gives you retained founder hours for fixes, iterations and the roadmap after launch.
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0515 minutes.
One quote.
Tell us what you need. We reply on WhatsApp or email with a time, and a written quote after the call.
Re: Data Pipeline & Warehouse
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