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Data and knowledge sharing for seamless and innovative engineering collaboration is critical to quick yield ramping. This paper presents the developments of a pragmatic methodology and a platform design for quick, flexible and collaborative composition and provision of engineering data analysis (EDA) services. The methodology combines Markov chain-based EDA procedure modeling and knowledge extraction with an identification method of re-usable service components from the EDA procedures. The platform adopts a service oriented architecture and web service technology to facilitate EDA service management and sharing. The design and developments are conveyed and supported by using a legacy EDA system and its usage data.