Define business goals first to avoid overbuilding pipelines that fail real startup needs..Choose data sources early, balancing batch processing simplicity with streaming requirements future growth..Design modular architecture so ingestion, transformation, and storage scale independently over time easily..Leverage cloud-managed services to reduce operational burden and enable automatic scaling safely globally..Implement data quality checks early to catch errors before analytics teams notice them..Support schema evolution because startup data models change faster than documentation expects today..Use orchestration tools to schedule pipelines, manage dependencies, and recover from failures automatically..Monitor performance metrics continuously to control costs as data volumes grow unexpectedly fast..Iterate often, keeping pipelines simple until product traction demands deeper complexity and scale..Read More Stories.Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp