ProjoMania

Business solutions

Data Migration & Integration

Move data between any systems, not just Odoo. Legacy migrations, M&A consolidation, cross-system pipelines. Audit trails included.

Qué hacemos

Data migration beyond Odoo

We built our migration discipline on Odoo, and we use the same discipline everywhere else. Moving data is structurally the same problem whether the source is Odoo, SAP, a 20-year-old on-prem application, or a stack of CSVs.

What “properly” looks like for a data migration

  • Audit first — row counts, foreign-key integrity, duplicate rate, PII inventory.
  • Target schema — designed for the system you are moving to, not copy-pasted from the source.
  • Mapping in code — every transformation lives in a version-controlled pipeline. No hand-run scripts on cutover day.
  • Validation — row counts match, aggregates tie out, critical business constraints verified.
  • Reconciliation report — the delta between source and target, explained.
  • Rollback — a reversible cutover by default.

Stacks we reach for

  • Airbyte (self-hosted or cloud) — off-the-shelf source connectors.
  • Fivetran — managed alternative when the finance model fits.
  • dbt — transformations, tests, docs.
  • PostgreSQL + partitions — the workhorse target for operational data.
  • ClickHouse / BigQuery / Snowflake — analytical targets.
  • Custom Python / Go — when the source has no connector and needs bespoke extraction.

Cronograma típico

Tres tamaños indicativos de engagement

Pequeño

3–6 weeks — single source, single target

Mediano

6–12 weeks — multi-source or complex transformation

Grande

12+ weeks — enterprise-scale migration

Cada cotización es a medida. Cómo funciona la tarificación →

FAQ

Preguntas comunes sobre data migration & integration

Which tools do you use? +

Custom ETL for bespoke shapes. Airbyte or Fivetran for off-the-shelf connectors. dbt for transformations. PostgreSQL / ClickHouse / BigQuery / Snowflake for targets depending on the workload.

Do you handle PII? +

Yes, with the controls a regulated environment requires — encryption in transit and at rest, narrow IAM, auditable access, retention policy. See the [security page](/en/legal/security/).

What about data quality? +

Baked in. We surface quality issues early — duplicate records, broken foreign keys, type mismatches — and fix upstream rather than hide them in the target.

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