This whitepaper explores the role of data science in modern industry, emphasizing its ability to turn vast, complex data into actionable insights. It highlights challenges across culture, security, and technology, noting that resistance to change and poor data quality often hinder adoption. Effective practices include cross-functional teams, central data science hubs, and agile “data trials” to quickly assess project viability. Applications range from predictive maintenance and condition monitoring to natural language processing and root cause analysis. Case studies in nuclear, aerospace, steel, and consulting show both successes and setbacks, underscoring the importance of collaboration, planning, and adaptable methods.

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