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Home / Glossary / Data stewardship

What is Data stewardship?

Data stewardship is the practice of managing, securing, and maintaining data integrity throughout its lifecycle. It involves overseeing data governance, quality control, compliance, and ethical usage, ensuring that data remains accurate, accessible, and aligned with business or regulatory requirements.

Related Glossaries

  • Data Lake Data lake refers to a centralized repository that stores structured, semi-structured, and unstructured data at any scale. It enables organizations to perform advanced analytics, machine learning, and big data processing while maintaining raw data integrity.
  • Leakage (machine learning) Leakage in machine learning refers to unintended exposure of information from training data into the model in a way that artificially inflates its predictive performance. It occurs when test data is improperly included in training or when future information leaks…
  • Unstructured Data Unstructured data refers to data that does not follow a predefined format, such as text, images, videos, and social media posts. It requires advanced processing techniques like NLP and deep learning for analysis.
  • Execution Drift Execution Drift refers to a change in AI behavior caused by shifts in execution context rather than by model updates. These shifts may come from changes in data state, prompt context, or pipeline structure.
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