Masaru Dobashi is a senior expert in distributed computing and data sharing, with over 12 years leading R&D and technical strategy for cross-enterprise data spaces and large-scale analytics platforms. He has driven system integration and operations for Hadoop-like ecosystems—Hadoop, Spark, Storm, Kafka—operating Spark at thousands-core scale and designing low-latency distributed stream processing systems. As a technical leader and consultant at NTT DATA and now IPA while also serving as a visiting researcher at the University of Tokyo, he blends enterprise delivery with academic rigor. He is an accomplished author and speaker on topics from Apache Spark and Kafka to Dataspace architectures (IDS, Gaia-X, EDC) and has contributed white papers and books that bridge theory and production. Less obvious: he combines deep fault-investigation experience (Kafka failure modes) with practical usage-control and connector work for trusted inter-company data exchange. His background positions him to translate cutting-edge research into resilient, enterprise-grade data infrastructure.
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