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High-quality data is indispensable for informed decision-making, operational efficiency, customer satisfaction, regulatory compliance, and innovation. Decision-makers use data to analyze trends, understand market dynamics, and forecast future developments. Risk Management Risk management is another domain where data quality is crucial.
It shows clear attempts to move exports away from EU markets to elsewhere in the world. The data showed that the smallest exporters were shifting up to 46% of their export growth from the EU to other markets since the referendum in 2016, with slightly larger firms shifting around 19% of their exports. Gravity defying. Tariff barriers.
The speed and agility it permits lend themselves to discovery environments such as life sciences R&D and target marketing activities within financial services. To date, most Big Data accomplishments have involved operational cost savings or allowing the analysis of larger and more diverse sets of data.
Think of the colleges that are increasingly able to identify students at risk of dropping out and intervene before they do. Or lenders’ enhanced abilities to gauge creditrisk. Energy, agriculture, insurance, retail, human resources — no industry is unaffected. The options are tangible.
Ash Gupta is President of Global CreditRisk and Information Management at American Express, and Guy Peri is Chief Data Officer and Vice President of Information Technology at P&G. Both are addressing cognitive applications that benefit customers and bring operational business value to their own organizations.
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