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For data teams and businesses to get the most out of operational and analytical data, many organizations today are turning to Data Mesh as their go-to organizational, architectural and technological approach. Why? Data teams today face enormous cognitive and process pains of their existing data architectures: Vendor lock-in, data consistency and quality, as well as significant delays from time-to-insight.
Founder of the Data Mesh paradigm Zhamak Dehghani sums up Data Mesh perfectly as, “A decentralized sociotechnical approach in managing and accessing analytical data at scale.”
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