Data warehouse and ETL pipelines: every system in one place, refreshed on schedule
We build data warehouses and ETL pipelines turnkey. Data from SAP, Odoo, CRM, POS, banks and ad platforms lands daily in one clean, consistent store. Reporting, BI and AI models run on top of it.
What hurts
Your data lives in a dozen systems: ERP, CRM, POS, warehouse, bank, ad accounts. To answer a simple question about margin by channel, an analyst spends a week exporting and stitching files.
Reports run straight against the production ERP database. A heavy query slows it down during business hours, and finance complains. Nobody keeps history, so comparing with last year is guesswork.
The export scripts were written by one developer years ago. That developer left, and there is no documentation. When something breaks overnight, every report shows zeros in the morning and nobody knows why.
What we build
- Source audit: what exists, how often it changes, who owns it
- Warehouse architecture on PostgreSQL, BigQuery or ClickHouse sized to your volume
- ETL pipelines from SAP, Odoo, Dynamics, CRM, POS, bank APIs and ad platforms
- dbt models with data quality tests at every step
- Change history for period-over-period comparison
- Refresh schedules with retries when a source fails
- Pipeline monitoring with alerts to Microsoft Teams, Telegram or email
- Role-based access and an audit log of who read what
What you get
- A working warehouse in your cloud account or on your server
- Pipeline and dbt model code in your repository
- A data catalog: tables, fields, sources, owners
- A pipeline health dashboard with configured alerts
- A runbook for common failures and team training
How we measure the result
- Data freshness: hours from event to warehouse
- Pipeline failures per month and time to recover
- Share of data quality tests passing each day
- Analyst time spent preparing a standard report
Systems and stack
Industries
Questions
How much does a data warehouse and ETL project cost?
From $10,000. The price depends on the number of sources, whether they have APIs, data volume and freshness requirements. Daily refresh from five systems costs less than near real time from twenty. You get a fixed estimate 2-3 days after discovery. Any overrun caused by us is finished at our own cost.
How long does it take?
Between 6 and 12 weeks. The first sources are connected and visible by week 2 or 3. Then we add systems one at a time, each one verified. Timelines usually stretch because of sources without APIs that need file-based exchange.
Which systems do you connect?
SAP, Odoo, Microsoft Dynamics, HubSpot, Pipedrive, Shopify, WooCommerce, POS systems, bank APIs, Google Ads, Meta Ads and GA4. For systems without an API we set up scheduled file exchange. We never load the production ERP during business hours.
Where is our data stored?
Wherever you decide: in your own cloud account, on your own server, or on a dedicated server in the EU (Hetzner, Germany). We sign an NDA and a GDPR DPA and work under ISO/IEC 27001:2022. Access is role-based and reads are logged.
Which warehouse should we choose?
PostgreSQL suits most mid-size companies and is cheap to run. BigQuery is convenient if you already use Google Ads and GA4. ClickHouse is our choice for heavy event streams. We recommend after measuring your volumes, not from a favourite tool.
Who runs the warehouse after launch?
We hand over the code, the data catalog and the runbook, so your team can run it. Or we keep it under an SLA: pipeline monitoring, reacting to source failures, connecting new systems. We also track API changes in third-party services.
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Describe the task. The first call is with the founder.
We reply within one business day. 30 minutes to tell you whether it is worth doing and what it costs.