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AIOps vs. MLOps: Harnessing big data for “smarter” ITOPs

IBM Journey to AI blog

Primary activities AIOps relies on big data-driven analytics , ML algorithms and other AI-driven techniques to continuously track and analyze ITOps data. The process includes activities such as anomaly detection, event correlation, predictive analytics, automated root cause analysis and natural language processing (NLP).

Big Data 106
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What Do Data Scientists Do? A Guide to AI Maturity, Challenges, and Solutions

DataRobot Blog

Once an organization has identified its AI use cases , data scientists informally explore methodologies and solutions relevant to the business’s needs in the hunt for proofs of concept. These might include—but are not limited to—deep learning, image recognition and natural language processing. BARC ANALYST REPORT.