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Last updated: March 16, 2026, 5:30 AM ET

Data Governance & Causal Modeling

Data practitioners face a mandatory shift toward human-in-the-loop oversight by 2026, demanding architectures that support active metadata and European data sovereignty compliance, according to analyses of future governance standards. Concurrently, to advance analytical rigor beyond mere correlation, data scientists are advised to master six advanced causal inference methods in Python, including doubly robust estimation and instrumental variables, to better model treatment effects.