Database Data warehouse ETL / scripts Query Application Data lake
Provenant
Platform · Provenant

Faster, error-aware migration.

Provenant applies structure-preserving transforms so data migration, reconciliation, and query translation are faster and more automated — any-to-any models, multi-dialect queries, views, referential integrity checks, and versioning.

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Ekam
Module 01 · Ekam

Instant data science pipelines.

Drop in feature definitions and get provenant dataframes with source mapping, ETL, provenance, and cell-level quality checks — reusable and composable.

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  • Built-in source mapping and ETL
  • Provenance tracked with the frame
  • Cell-level data quality checks
Datalake
Module 02 · Datalake

The alpha model for data lakes.

Automatically create lake models that stay faithful to source data, relations, and constraints — so lake investments become usable at scale.

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  • Source, relation, and constraint fidelity
  • Models that scale with lake growth
  • Less drift between domain knowledge and engineering
Model
Module 03 · Model

Warehouse migration with a live model.

Move off expensive legacy DWH to cloud with a model that stays a reflection of reality — evolving, repairing, and faithful as sources change.

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  • Legacy → cloud DWH programmes
  • Constraint and data fidelity checks
  • Unified model across time, not just systems
Integer
Module 04 · Integer

ETL unlock — DevOps-ready code.

Free proprietary ETLs into Spark or other modern pipelines with composable, evolving models — and confidence checks after the move.

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  • Proprietary → portable ETL translation
  • Composable, live transformation models
  • Sanctity checks after cutover
Data
Module 05 · Data

Database migration without the FK theatre.

Move databases to cloud without endless dependency studies and foreign-key switch-off sequences — with automated checks for data and constraint fidelity.

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  • Any-to-cloud database programmes
  • Dependency-aware cutovers
  • Referential integrity validation
How it differs
01 / Fidelity

Structure-preserving by design.

Provenant targets mathematical guarantees on relations and constraints — not hope-and-check spreadsheets.

02 / Velocity

Less rear-view cross-checking.

Automated validation and reconciliation compress the painful middle of every migration programme.

03 / Provenance

Cell, row, and column awareness.

Know where data came from and how it transformed — especially in science and lake workloads.

04 / Automation

Dialects, views, and scripts.

Query and ETL translation across many dialects so engineers ship platforms, not rewrites.

FAQ

Migration, straight answers.

What can Provenant migrate?

Databases, data warehouses, application data models, ETLs and scripts, views, and queries across many dialects — plus lake models and science pipelines via Ekam, Datalake, Model, Integer, and Data.

How is this different from manual ETL rewrites?

Provenant targets structure-preserving transforms with automated validation and reconciliation, so teams spend less time on rear-view cross-checks and dependency theatre.

Do you guarantee 100% accuracy?

Provenant is built for high-fidelity, structure-preserving moves with automated checks. We attribute product claims to Provenant and agree acceptance criteria with you on a discovery call — we don't invent guarantees.

How long does a migration take?

It depends on source complexity, dialects, and volume. Provenant aims to compress effort versus typical manual programmes; we size phases after a short discovery.

Can we start with one module?

Yes. Start where the pain is — Data (databases), Integer (ETL), Model (warehouse), Datalake, or Ekam — then expand under the Provenant umbrella.

What's next

Migrated. Now run it.

Clean data still needs systems, growth, and automation. Pair Migrate with the other pillars when you're ready.

01

Build the surfaces.

03

Run the systems.

04

Automate the busywork.

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