Sasi Chandru is a data governance and advisory lead with extensive experience implementing complex data solutions for major companies like Halvik, Nike, EY, and Wells Fargo. His expertise spans Databricks, Collibra, data quality, and data architecture. He is currently pursuing a PhD at Capitol Technology University.
Sasi is deeply interested in the societal and ethical implications of technology. He frequently writes about AI ethics, the future of work, and global AI regulation. He explores philosophical concepts like phenomenology in the context of artificial intelligence and reads about qualitative research methodologies.
Unique fact: Sasi succinctly describes his work with the mantra: "design, develop, demo, deploy, document, data govern".
Read the full overview →They are not very likely to become strong advocates of your product or service They have a unique set of diverse traits where they are decisive and methodical but can sometimes be extra cautious and skeptical They focus on the results, but can still be quite procedural and analytical about how to get there
Calculativeness (C) reflects the degree to which a person is likely to be cautious, systematic and analytical. Those scoring high tend to emphasise quality and accuracy.
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