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Key Takeaways Data Engineering is vital for transforming raw data into actionable insights. Key components include data modelling, warehousing, pipelines, and integration. Effective datagovernance enhances quality and security throughout the data lifecycle. What is Data Engineering?
By 2026, over 80% of enterprises will deploy AI APIs or generative AI applications. AI models and the data on which they’re trained and fine-tuned can elevate applications from generic to impactful, offering tangible value to customers and businesses.
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