Our enterprise data challenges: siloed data, inconsistent representation, and varies levels of quality
Our vision and strategy to build a clean data platform in an incremental way: clean data definition, paved road data pipeline to cleanse data, tools automation for the single representation of data, data type standardization, single source of truth entities, and relationship, supporting contextual variability and extension.
The potential role Semantic Technology could play: elevate clean model to a semantic fit-for-purpose rich knowledge graph
Our lessons from early exploration: value proposition, developer experiences, and adoption.
Opportunities to the Semantic Technology Industry: standardization, practical application to large scale data, e2e solution and developer experience, and adoption.
Hands-on full-stack innovator, strategic thinker, leader and evangelist for new technology and product, with 25+ years of experience covering a wide range of technology areas: from highly scalable distributed database engine, B2B e-commerce services, to consumer-facing financial applications on multiple platforms and devices, in various environments ranging from advanced research group in unive