2 posts
toss 안녕하세요, 토스플레이스에서 Data Platform Team을 이끌고 있는 박종익입니다. "인사이트는 분명히 나왔는데, 왜 실행은 느릴까요?" 데이터 조직에 있다 보면 이 질문을 자주 마주하게 됩니다. 분석은 쌓이고, 대시보드는 채워지는데 — 정작 제품이나 사업에 직접적인 변화가 일어나는 속도는 기대에 미치지 못하는 경우가 많아요. 저희도 같은 고민을 오랫동안 해왔습니다. 그 고민에서 시작한 것이 바로 Metric Review입니다. 오늘은 저희가 왜 Metric Review를 시작했고, 어떻…
coupang Coupang has developed an internal SCM Workflow platform to streamline the complex data and operational needs of its Supply Chain Management team. By implementing low-code and no-code functionalities, the platform enables developers, data scientists, and business analysts to build data pipelines and launch services without the traditional bottlenecks of manual development. ### Addressing Inefficiencies in SCM Data Management * The SCM team manages a massive network of suppliers and fulfillment centers (FCs) where demand forecasting and inventory distribution require constant data feedback. * Traditionally, non-technical stakeholders like business analysts (BAs) relied heavily on developers to build or modify data pipelines, leading to high communication costs and slower response times to changing business requirements. * The new platform aims to simplify the complexity found in traditional tools like Jenkins, Airflow, and Jupyter Notebooks, providing a unified interface for data creation and visualization. ### Democratizing Access with the No-code Data Builder * The "Data Builder" allows users to perform data queries, extraction, and system integration through a visual interface rather than writing backend code. * It provides seamless access to a wide array of data sources used across Coupang, including Redshift, Hive, Presto, Aurora, MySQL, Elasticsearch, and S3. * Users can construct workflows by creating "nodes" for specific tasks—such as extracting inventory data from Hive or calculating transfer quantities—and linking them together to automate complex decisions like inter-center product transfers. ### Expanding Capabilities through Low-code Service Building * The platform functions as a "Service Builder," allowing users to expand domains and launch simple services without building entirely new infrastructure from scratch. * This approach enables developers to focus on high-level algorithm development while allowing data scientists to apply and test new models directly within the production environment. * By reducing the need for code changes to reflect new requirements, the platform significantly increases the agility of the SCM pipeline. Organizations managing complex, data-driven ecosystems can significantly reduce operational friction by adopting low-code/no-code platforms. Empowering non-technical stakeholders to handle data processing and service integration not only accelerates innovation but also allows engineering resources to be redirected toward core architectural challenges.