SnowConvert AI - Informatica PowerCenter

SnowConvert AI automatically converts Informatica PowerCenter to Snowflake. It reads your exported PowerCenter repository (the mappings, workflows, transformations, and expressions) and produces runnable Snowflake code, so you can migrate data pipelines without rewriting them by hand.

This guide is the translation reference: it explains how each Informatica element maps to Snowflake, what the generated code looks like, and where to review manual follow-ups. Use it alongside the ETL Migration user guide, which covers the end-to-end migration process, prerequisites, and how to run a conversion.

How Informatica concepts map to Snowflake

The following table maps each Informatica concept to its Snowflake or dbt counterpart:

Informatica PowerCenterSnowflake / dbtDescription
WorkflowTask graphThe orchestration order becomes a graph of Snowflake Tasks.
SessionSnowflake Task that runs a MappingEach Session runs its Mapping’s dbt project (or calls its procedure).
WorkletStored procedureA reusable sub-workflow becomes a stored procedure the Task graph calls.
Mappingdbt projectThe data flow becomes a standalone dbt project of models.
Transformationdbt modelEach transformation becomes a SQL model (a SELECT, join, or CTE).
Mappletdbt macroA reusable transformation group becomes a macro.
Source and Source QualifierStaging modelSource reads become stg_ staging models that read from the tables defined in sources.yml.
TargetMart modelTargets become the business-ready marts models.
Mapping and Workflow variablescontrol_variables tableVariables and parameters move to a runtime control table.
Expression functionSnowflake SQL functionBuilt-in functions convert to Snowflake equivalents.

Output formats

SnowConvert AI produces two output formats. The generated Snowflake code differs by format, so this guide documents each one separately:

Output formatStatusWhat you getReference
dbt projectGenerally availableEach Mapping becomes a dbt project; Workflows become Task graphs that run those projects.Informatica to dbt
Snowflake ScriptingPreview, in active developmentEach Mapping becomes a Snowflake stored procedure; Workflows call those procedures directly.Informatica to Snowflake Scripting

Several references are shared across both output formats, because the orchestration and the generated Snowflake expressions are the same regardless of format:

Supported components at a glance

The tables below list the Informatica components SnowConvert AI recognizes and which output formats support them today. Unlisted components generate an EWI code that flags the component for manual conversion.

Mapping transformations (data flow)

TransformationdbtSnowflake Scripting
Source DefinitionAvailableAvailable
Source QualifierAvailableAvailable
ExpressionAvailableAvailable
Target DefinitionAvailableAvailable
FilterAvailablePlanned
JoinerAvailablePlanned
Lookup (connected and unconnected)AvailablePlanned
AggregatorAvailablePlanned
RouterAvailablePlanned
SorterAvailablePlanned
UnionAvailablePlanned
NormalizerAvailablePlanned
RankAvailablePlanned
Sequence GeneratorAvailablePlanned
Update StrategyAvailablePlanned
Stored ProcedureAvailablePlanned
MappletAvailablePlanned

Workflow elements (control flow)

ElementdbtSnowflake Scripting
Workflow and Start taskAvailableAvailable
SessionAvailableAvailable
Session overrides (Pre/Post-SQL, SQL Override)AvailableAvailable
WorkletAvailableAvailable
Decision, Assignment, and Email tasksAvailableAvailable
Variable and parameter managementAvailableAvailable

Note

The Snowflake Scripting output format is in active development. For data-flow transformations it currently emits Source, Source Qualifier, Expression, and Target; other transformations are converted in the dbt format today. See Informatica to Snowflake Scripting for the current status.

Naming and sanitization rules

To keep generated dbt model names and ref() calls valid and aligned, SnowConvert AI sanitizes Informatica object names: any character outside AZ, az, 09, and the underscore (_) is replaced with an underscore. Letter case is preserved.

Informatica nameGenerated name
SQ_DimCurrencySQ_DimCurrency
m_load-customer datam_load_customer_data
LKP@CurrencyLKP_Currency

dbt models follow the three-tier naming convention: staging models use the stg_raw__ prefix, intermediate models use the int_ prefix, and mart models take the target table name. See Informatica to dbt for details.

Get started

  1. Read the ETL Migration user guide for prerequisites and how to run a conversion.
  2. Choose your output format: Informatica to dbt (generally available) or Informatica to Snowflake Scripting (preview).
  3. Use the shared Expression functions and Data types references as you review the generated code.