Remove Machine Learning Remove Predictive Modeling Remove Strategy Remove Uncertainty
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Real-time Data, Machine Learning, and Results: The Evidence Mounts

CIO Business Intelligence

By Bryan Kirschner, Vice President, Strategy at DataStax. From delightful consumer experiences to attacking fuel costs and carbon emissions in the global supply chain, real-time data and machine learning (ML) work together to power apps that change industries. more machine learning use casesacross the company.

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Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability

DataKitchen

The uncertainty of not knowing where data issues will crop up next and the tiresome game of ‘who’s to blame’ when pinpointing the failure. Running these automated tests as part of your DataOps and Data Observability strategy allows for early detection of discrepancies or errors. One of the primary sources of tension?

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Oshkosh puts digital solutions into overdrive

CIO Business Intelligence

How extensive is your data-driven strategy today? An example of that enterprise-level digital strategy and alignment process was the creation of three advanced capabilities: AI and analytics, intelligent automation, and digital manufacturing. Khare: I look at uncertainty at two tiers.

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Oshkosh puts digital solutions into overdrive

CIO Business Intelligence

How extensive is your data-driven strategy today? An example of that enterprise-level digital strategy and alignment process was the creation of three advanced capabilities: AI and analytics, intelligent automation, and digital manufacturing. Khare: I look at uncertainty at two tiers.

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How to Set AI Goals

O'Reilly on Data

Technical competence results in reduced risk and uncertainty. As AI maturity increases, a non-incremental, holistic, and organization-wide AI vision and strategy should be created to achieve hierarchically-aligned AI goals of varying granularity—goals that drive all AI initiatives and development. Conclusion.

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Enhance your Lending with Predictive Analytics

BizAcuity

Credit scoring systems and predictive analytics model attempt to quantify uncertainty and provide guidance for identifying, measuring and monitoring risk. Benefits of Predictive Analytics in Unsecured Consumer Loan Industry. Predictive Analytics enhances the Lending Process.

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How Skullcandy Uses Predictive and Sentiment Analysis to Understand Customers

Sisense

We fed Kraken (BigSquid’s predictive analytics engine) information about historical warranty costs, claims, forecasts, historical product attributes, and attributes of the new products on the roadmap. Then we ran Kraken’s machine learning and predictive modeling engine to get the results.