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Bolster analytics with machine learning
Advanced analytics has become a necessity for businesses to gain deep insights that drive better decisions. In parallel, advancements in the field of analytics, as in any new technology, are evolving at a rapid pace. Among them, investing in machine learning (ML) is a safe bet, says Anu Jain, Vice President, Americas and leader at Teradata, a leading analytics and consulting services company based in Atlanta, USA.
ML can help computers explore past experiences, parse data and learn from the experiences on their own. Therefore, if an enterprise is in the business of making or selling products or services or anything in between, ML can augment the process of analytics. For instance, ML can be used to build predictive models of customer segment likely to churn, demand forecasts, financial performances, etc. ML can also be used for segmenting customers, event analysis, data integration, anomaly detection and many more.
Leveraging ML for analytical activities can help discover expected outcomes and outcomes that can be leveraged to optimize operations.
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