Automated analysis of the existing data landscape

• Smart analyzer: Analyzes ETL landscape, code inventory, workstreams, job design, connections, and complexity
• Schedule analyzer: Evaluates job scheduler capabilities, scheduling, observability, alert mechanisms, recoverability, and restartability
• Dependency analyzer: Assesses job and workflow dependencies, schedule dependencies, functional dependencies, and lineage
• Job analyzer: Analyzes job functionality, orchestration, performance, availability, exception handling, recoverability, and resilience

Automated analysis, parsing, conversion, validation, and deployment of ETL jobs to Informatica Cloud

• ETL parse: Automates metadata parsing and transformation from legacy ETL jobs to IDMC
• ETL convert: Automates conversion and generates conversion reports
• Smart validate: Reconciles and validates migrated data
• Smart deploy: Automates deployment of validated IDMC codes

Provides insights into platform health, covering observability, cost, and performance

• Health check/observability: Monitors data pipelines/workflows for troubleshooting
• Cost monitoring: Provides near real-time IPU usage insights for proactive decision-making
• Optimization: Streamlines data analysis and optimizes resource allocation to save time and cost for IT teams

Ensures data trust with a comprehensive framework

• Trust readiness assessment: Offers assessment reports with solution approaches and target state models
• Trust strategy: Provides metadata lineage, data quality framework, data governance blueprint, and data security/privacy policies
• Trust framework deployment: Delivers a data trust roadmap, DG blueprint, metadata and lineage documents, and data security architecture