Complex ETL and Transformations
Design, orchestrate, and monitor sophisticated ETL and ELT workflows with multiple steps, nested flows, and complex transformations across any source or destination.
Why it matters: Complex transformations are often essential for preparing data for analytics, compliance, or operational workflows—without them, insights can be incomplete or inaccurate.
- Complex Workflows
 - Transformations and Mapping
 - SOC 3 Report (SOC 2 Report available after NDA)
 - Security Policies
 
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Why Etlworks
Multi-step workflows: Build nested flows with conditionals, loops, error handling, and parallel execution.
Advanced transformations: Apply mappings, scripts, filters, and calculated fields using SQL, JavaScript, or Excel-like logic.
Real-time or batch: Run flows on a schedule, on demand, or in response to events and changes (CDC).
Broad format support: Transform flat files, JSON, XML (including deeply nested structures), and binary data.
Mapping at scale: Use external mapping files, reusable transformation blocks, and prebuilt components.
Enterprise-grade performance: Optimize throughput with automatic partitioning, multithreading, and bulk loading.
How Companies Use Etlworks for Complex ETL and Transformations
                        
                            OpenGov, a leader in cloud software for local governments, uses Etlworks to
                            power hundreds of complex pipelines across customer environments. With multi-step workflows,
                            reusable templates, and real-time monitoring via Grafana, they reduced onboarding time by
                            90%.
                            
                            Read
                                the case study
                        
                            Universal Music Group (UMG), the world’s leading music company, needed to
                            sync MySQL data with AS400 systems. Etlworks delivered transactional consistency and complex
                            transformations using JavaScript through a CDC pipeline built for reliability.
                            
                            Read
                                the case study
                        
                            AMK Cambodia, a leading microfinance institution, turned to Etlworks for
                            integrating complex XML from Oracle and Postgres into normalized Oracle warehouse tables.
                            Advanced features like SQL*Loader, auto partitioning, and externalized mappings made it
                            seamless.
                            
                            Read
                                the case study
                        
                        
                            RecBi, a business intelligence provider, uses Etlworks for complex
                            multi-step integrations across APIs, Salesforce, databases, email, GCP, and files. Their
                            dynamic pipelines support multiple customers in one run, delivering flexibility and speed.
                            
                            Read
                                the case study
                        
                
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