Webhooks let systems push events as they happen—avoiding the waste and delay of frequent polling. In a scenario analyzed by Svix , only 1.5% of polling requests returned updates, which...

Introduction It’s Tuesday morning; the data team at a Fortune 500 manufacturing giant receives an urgent request from the sales organization. Customer territories need to be recalibrated based on real-time...

Key Takeaways For legacy ERP on Sybase ASE, ETL lives or dies by source safety and governance. Plan for log-based CDC , idempotent loads & dedupe , schema evolution ,...

Key Takeaways Edge ETL succeeds when it embraces embedded, offline-first constraints. SQLite’s in-process engine, single-file storage, and ACID transactions make it a natural fit for device-local capture and transformation, with...

Key Takeaways No-code ELT moves transforms into the warehouse. Teams load raw data first and then use cloud-warehouse compute for transformations—simplifying architecture and speeding time-to-insight; ETL vs. ELT summarizes the...

Key Takeaways At big-data scale, ETL lives or dies by throughput and resilience. Plan for high volume/variety/velocity, schema evolution, late-arriving events, idempotent writes & dedupe, smart partitioning, and CDC/streaming +...

Key Takeaways CRM ETL succeeds when it respects each CRM’s object model and API quotas. Plan for contacts/companies/accounts/leads/opportunities/custom objects , associations , deduplication & idempotent writes , schema evolution ,...

Key Takeaways Azure ETL is shaped by platform primitives and service limits. Successful pipelines account for ADLS/Synapse/SQL/Functions/Event Hubs , integration runtimes , schema drift , and cost-aware orchestration —plus options...

Key Takeaways SAP ETL is shaped by its application-layer interfaces and system limits. Successful pipelines account for BAPIs/RFCs/IDocs , HANA pushdown , complex table structures , and deduplication , with...