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informatica-assessment
// Analyze Informatica Power Center workflows/mappings from SnowConvert ETL.* outputs and source XML files. Classifies workflows, scores migration complexity, and produces JSON for the parent assessment multi-report.
// Analyze Informatica Power Center workflows/mappings from SnowConvert ETL.* outputs and source XML files. Classifies workflows, scores migration complexity, and produces JSON for the parent assessment multi-report.
Deploy and validate all object types (tables, views, functions, procedures) in dependency order. Triggers: deploy objects, migrate objects, deploy tables, deploy views, migrate functions, migrate procedures.
End-to-end database migration to Snowflake. Orchestrates the full migration lifecycle from source connection through initial conversion. Triggers: migrate, migration, migrate to snowflake, end to end migration, e2e migration, full migration.
Analyzes Dynamic SQL occurrences from SnowConvert issues, classifies patterns, scores complexity, and records migration considerations. Use for SQL Server, Redshift, Oracle, or Teradata to Snowflake migrations. Driven entirely by `scai assessment sql-dynamic`; no custom scripts.
Analyze SSIS packages from SnowConvert ETL.* outputs and source .dtsx files. Classifies packages, scores migration complexity, and produces JSON for the parent assessment multi-report.
Analyzes workloads to be migrated to Snowflake using SnowConvert assessment reports. Routes to specialized sub-skills for high-quality assessments. Use this skill when user wants to do an assessment of their code or ETL workload, waves generation, object exclusion, sql dynamic and/or ETL analysis (SSIS)
Analyze SQL object dependencies and create deployment waves/partitions for database migrations. Use when working with SQL migration planning, SnowConvert outputs, or deployment wave creation.
| name | informatica-assessment |
| description | Analyze Informatica Power Center workflows/mappings from SnowConvert ETL.* outputs and source XML files. Classifies workflows, scores migration complexity, and produces JSON for the parent assessment multi-report. |
| parent_skill | assessment |
| license | Proprietary. See License-Skills for complete terms |
SnowConvert AI migrates Informatica Power Center workflows to Snowflake. This skill analyzes workflows and mappings from their source XML and SnowConvert assessment CSV reports to generate detailed migration analysis including workflow classification and complexity assessment.
Use ONLY Provided Scripts
python -m informatica_assessment_analyzerQuality Over Speed
Follow ONLY Provided Analysis Methods
Complete ALL Steps
Report Generation via Parent Skill ONLY
../SKILL.md) is the ONLY approved method--informatica-json parameter pointing to the informatica_assessment_analysis.json file generated by this skillCopy this checklist and track your progress:
Analysis Progress:
- [ ] Step 1: Locate and Validate Input Files
- [ ] Step 2: Generate JSON Analysis
- [ ] Step 3: Analyze Informatica workflows (sub workflow)
- [ ] Step 4: Draft AI summary (HTML AI summary)
Do NOT prompt the user for paths. Inputs are resolved automatically from project_dir configured by the parent assessment skill:
| Input | Auto-resolution |
|---|---|
ETL.Elements.csv | Latest <project_dir>/reports/SnowConvert/ETL.Elements.*.csv |
ETL.Issues.csv | Latest <project_dir>/reports/SnowConvert/ETL.Issues.*.csv |
| Informatica source dir | The --etl-replatform-sources-path recorded by convert (or <project_dir>/source/etl/, falling back to whatever was passed to scai code convert) |
| Output dir | <project_dir>/assessment/informatica/ (create if missing) |
Validation (silent — only surface a problem to the user if validation fails):
ETL.* CSVs exist. If they don't, the conversion either skipped ETL or didn't include the --etl-replatform-sources-path flag — return to the parent and ask the parent to re-run convert with ETL inputs..xml files (PowerCenter XML exports).Run with the auto-detected paths from Step 1:
uv run python -m informatica_assessment_analyzer <ETL.Elements> <ETL.Issues> <OUTPUT> [--source-dir <XML_SOURCE_DIR>]
The --source-dir flag enables CONNECTOR extraction from the Informatica XML, enriching the analysis with data flow edge details.
This step is a sub workflow to analyze workflows individually. After this, continue with step 4.
Important: To analyze workflows, follow the detailed instructions in references/writing_analysis.md. This reference explains:
For each pending workflow:
uv run python -m informatica_assessment_analyzer informatica <JSON_PATH> pending
Analyze the workflow:
Write analysis following the mandatory format in references/writing_analysis.md.
Note: Analysis is validated. If format is wrong, the command will fail with guidance.
Update the workflow with AI analysis:
uv run python -m informatica_assessment_analyzer informatica <JSON_PATH> update <WORKFLOW_PATH> \
--ai-status DONE \
--classification "Data Transformation" # or: Ingestion, Configuration & Control, Mixed: Ingestion + Transformation
--ai-analysis "<ANALYSIS_TEXT>"
DO NOT SKIP THIS STEP. The AI Summary is required before finishing the assessment.
Required Actions:
uv run python -m informatica_assessment_analyzer informatica <JSON_PATH> summary
Read the guide: references/ai_summary_guide.md
Generate summary file: ai_informatica_summary.html
<!DOCTYPE>, <html>, <head>, <body>, or <h1> tags. The report generator provides the section heading (<h2>AI Summary</h2>) automatically.Register the summary in the JSON:
uv run python -m informatica_assessment_analyzer informatica <JSON_PATH> ai-summary ai_informatica_summary.html
Verification Checklist:
ai_informatica_summary.html file existsai-summary commandCompletion: Report to user:
<output_path>/informatica_assessment_analysis.json