delivered for clients · names withheldmigration Data and analytics

Informatica PowerCenter to IDMC or dbt

Cohash moves PowerCenter estates to Informatica IDMC Cloud Data Integration, to dbt running inside the warehouse, or to a mix of both. We export the repository, sort every mapping and workflow into convert, rebuild or retire, and run old and new pipelines side by side until outputs match row for row. The scheduler, parameter files and shell scripts around PowerCenter move too, so nothing depends on the old servers.

  1. 01Repository export and usage
  2. 02Decide per mapping
  3. 03Convert and rebuild
  4. 04Runtime and connectivity
  5. 05Parallel run
  6. 06Scheduler cut-over and shutdown
case-study / informatica-powercenter-to-cloud delivered
beforeInformatica PowerCenter (self-managed) afterInformatica IDMC or dbt on the warehouse
01 · SOURCES 02 · INTEGRATION 03 · WAREHOUSE 04 · CONSUMERS On-premises databases On-premisesdatabases File and SaaS sources File and SaaSsources Orchestrator: replaces pmcmd and cron Orchestrator replaces pmcmdand cron IDMC Cloud Data Integration: multi-source mappings IDMC CloudDataIntegration multi-sourcemappings IDMC Secure Agent: near on-premises sources IDMC SecureAgent nearon-premisessources Warehouse loaders: ingestion without Informatica Warehouseloaders ingestionwithoutInformatica Cloud warehouse: Snowflake · Databricks · Fabric Cloud warehouse Snowflake · Databricks· Fabric dbt models: tests · docs · pull requests dbt models tests · docs · pullrequests Reports Reports
case file

The story

Told without the client's name or anything that could identify them.

what happened

A health plan's data engineering group still ran a large PowerCenter estate on servers with an old OS, even though its warehouse had already moved to the cloud. Nobody could say which mappings still fed a report, and the licence renewal was coming up. We exported the repository, joined it with run history and retired what never ran before estimating anything. Every remaining mapping got one decision: IDMC for multi-source mappings, dbt for reshaping data already in the warehouse. Old and new pipelines ran side by side until row counts and checksums matched, then the scheduler moved and the PowerCenter servers were turned off.

why it was urgent

Informatica has belonged to Salesforce since 18 November 2025. It runs a modernization program from PowerCenter to IDMC and also sells PowerCenter Cloud Edition. On the dbt side, v2 went generally available on 16 September 2026. End-of-support for PowerCenter depends on the version, and we look yours up in Informatica's support portal before planning.

problem statement
  • openThe PowerCenter servers run an old OS, and the upgrade path keeps getting deferred.
  • recurringSnowflake, Databricks or Fabric is the target, but data still comes in through an on-premises ETL tier.
  • blockedThousands of mappings exist, and nobody can say which ones still feed a report.
  • openRenewal talks have started, and the team wants a real IDMC-versus-dbt comparison first.
architecture

The estate, before and after

before
before

Before: an on-premises PowerCenter tier in front of a cloud warehouse

Everything bound for the cloud warehouse went through PowerCenter servers on an old OS. The workflows were started and fed by cron, an enterprise scheduler and shell scripts nobody had put in the repository.

Before: an on-premises PowerCenter tier in front of a cloud warehouse Everything bound for the cloud warehouse went through PowerCenter servers on an old OS. The workflows were started and fed by cron, an enterprise scheduler and shell scripts nobody had put in the repository. 01 · SOURCES 02 · ETL TIER 03 · TARGETS extract file renames trigger files pmcmd load queries On-premises databases Flat files renamed by shell scripts Shell scripts outside the repositoryexport Cron and enterprisescheduler pmcmd calls IN PowerCenter servers mappings · workflows ·old OS Cloud warehouse Snowflake · Databricks· Fabric Reports
Read the diagram as text
  1. On-premises databases → PowerCenter servers: extract
  2. Flat files → Shell scripts: file renames
  3. Shell scripts → PowerCenter servers: trigger files
  4. Cron and enterprise scheduler → PowerCenter servers: pmcmd
  5. PowerCenter servers → Cloud warehouse: load
  6. Cloud warehouse → Reports: queries
after
after

After: IDMC and dbt split the work, one orchestrator runs it

We run multi-source mappings in IDMC Cloud Data Integration, through Secure Agents placed near the on-premises sources. Transformations inside the warehouse are dbt models. A single orchestrator schedules both.

After: IDMC and dbt split the work, one orchestrator runs it We run multi-source mappings in IDMC Cloud Data Integration, through Secure Agents placed near the on-premises sources. Transformations inside the warehouse are dbt models. A single orchestrator schedules both. 01 · SOURCES 02 · INTEGRATION 03 · WAREHOUSE 04 · CONSUMERS extract mapping tasks load ingest load schedule schedule transform models On-premises databases File and SaaS sources Orchestrator replaces pmcmd and cron IN IDMC Cloud DataIntegration multi-sourcemappings IN IDMC Secure Agent near on-premisessources Warehouse loaders ingestion withoutInformatica Cloud warehouse Snowflake ·Databricks · Fabric dbt dbt models tests · docs · pullrequests Reports
Read the diagram as text
  1. On-premises databases → IDMC Secure Agent: extract
  2. IDMC Cloud Data Integration → IDMC Secure Agent: mapping tasks
  3. IDMC Secure Agent → Cloud warehouse: load
  4. File and SaaS sources → Warehouse loaders: ingest
  5. Warehouse loaders → Cloud warehouse: load
  6. Orchestrator → IDMC Cloud Data Integration: schedule
  7. Orchestrator → dbt models: schedule
  8. Cloud warehouse → dbt models: transform
  9. dbt models → Reports: models
results

What the client got

What changed for the client once the work was done. Described, not scored: we don't publish client figures.

  1. result 01

    Every mapping has one decision and a reason

    We marked each mapping, mapplet, session and workflow as convert, rebuild or retire, using run history and a read of what the mapping really does.

  2. result 02

    Warehouse logic lives in a dbt project

    We rebuilt the reshaping-only mappings as dbt SQL models, each with tests, sources and documentation, and they're reviewed in pull requests.

  3. result 03

    Outputs proven to match before switching

    During the parallel run we compared row counts, checksums and key aggregates per target table. Targets moved in batches, and only once they matched.

  4. result 04

    Nothing depends on the PowerCenter servers

    We moved the pmcmd calls, cron jobs and scheduler dependencies to the new orchestrator, archived the repository, and switched the PowerCenter servers off.

what can go wrong

Risks we plan for

  1. Logic with no SQL equivalent

    Java transformations, stored procedure calls, dynamic lookup caches and update strategies with complex conditions need redesigning if they move to dbt. A line-by-line translation won't work.

  2. Hidden dependencies

    The repository export won't show you the shell scripts that rename files, wait on triggers or call pmcmd. We find those by reading server crontabs and scheduler definitions.

  3. Paying twice

    PowerCenter and the new platform overlap during the parallel run. The order of batches should follow licence and server end dates, not only technical convenience.

  4. Roadmap under a new owner

    Salesforce plans to tie Informatica into Agentforce and Data 360, and packaging may shift as that happens. Write the contract and the architecture so you aren't locked in without a reason.

ai in this move

Where AI helps, and where it needs guardrails

Informatica's modernization program advertises AI-powered migration automation, and Salesforce plans to tie Informatica into Agentforce and Data 360. On our side, an LLM reads exported mapping XML and writes a plain-English spec plus a draft dbt model for each mapping. An engineer reviews it, and the parallel-run diff decides whether it ships. Agents work from exported metadata, not production credentials.

forward deployed engineers →
you keep

What you're left with

We write these for your setup, and they're working documents. Your team should be able to keep things running from them long after we've gone.

  • inventory01

    Mapping and workflow inventory with run history and a decision per object

    yours to keep
  • tests02

    Converted IDMC assets or dbt project with tests and documentation

    yours to keep
  • report03

    Parallel-run comparison report per target table

    yours to keep
  • plan04

    Scheduler and dependency map, with the new orchestration configuration

    yours to keep
  • plan05

    Decommission plan for PowerCenter servers and repository

    yours to keep
talent and delivery · informatica idmc or dbt on the warehouse

Certified engineers, wherever you need them.

Some clients want a project team, some want a couple of engineers on theirs. Either works. Onsite, nearshore or offshore, with handovers across time zones that keep things moving.

Onsite

Engineers at your sites in the US

Nearshore

Overlapping hours with US teams

Offshore

Overnight progress on your backlog

All time zones

Coverage handed over across time zones

24-hour coverage · US Central time
OnsiteUS business hours
Nearshoreoverlapping US hours
Offshoreovernight progress
Combinedhandover, not hand-off
01IDMC or dbt?

Often both. IDMC fits integration work: many sources, many targets, CDC and data quality rules. dbt fits transformations that run inside Snowflake, Databricks or Fabric. The split depends on what your mappings actually do, which the inventory shows.

02Can the conversion be automated?

Partly. Informatica's tooling and LLM-drafted dbt models handle routine mappings. Complex transformations and the scripts around PowerCenter still need engineers, and every converted pipeline is proven in a parallel run.

03Is PowerCenter going out of support?

It depends on your version. Informatica publishes end-of-support dates per version in its support portal. We look yours up before setting the timeline.

04Do you also handle data quality and MDM?

Yes. If Informatica Data Quality or MDM rules sit alongside PowerCenter, we inventory them in the same pass and decide where each rule should live.

sources 4 sources linked last checked 2026-10-20 content fingerprint 25c5d923
  1. 01Salesforce: Salesforce completes acquisition of Informatica (18 Nov 2025)salesforce.com ↗
  2. 02Informatica: PowerCenter to Cloud Modernizationinformatica.com ↗
  3. 03dbt docs blog: dbt v2 is GA (16 Sep 2026)docs.getdbt.com ↗
  4. 04dbt Labs: licensing FAQgetdbt.com ↗
Reviewed by the Cohash team Product names are trademarks of their owners. how we handle facts and data →
next step

Planning this move?

A 30-minute working session with a senior engineer. No slides.

useful to bring
  • The platform and the version you're on
  • Where you need to get to, and by when
  • What's custom: rules, plugins, integrations
  • Any audit finding or deadline driving it