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Decision Making with Uncertainty Requires Wideward Thinking

Andrew White

COVID-19 and the related economic fallout has pushed organizations to extreme cost optimization decision making with uncertainty. As a result, Data, Analytics and AI are in even greater demand. Demand from all these organizations lead to yet more data and analytics. With data comes quality issues. Everything Changes.

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Real-time Data, Machine Learning, and Results: The Evidence Mounts

CIO Business Intelligence

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. Data architecture coherence. Putting data in the hands of the people that need it.

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How Skullcandy Uses Predictive and Sentiment Analysis to Understand Customers

Sisense

Mark’s team is constantly adapting to and meeting the challenges of a rapidly evolving business using cloud technologies, real-time analytics, data warehousing, and virtualization. What if we could use this data to focus our resources and deliver better products? Using Sentiment Analytics to Inform New Product Design Decisions.

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IT leaders embrace the role of business change maker

CIO Business Intelligence

You have to truly understand how systems are used, how data is entered into systems, and how it’s manipulated in order to make decisions. The effort resulted in an enterprise data platform used to track users wherever they are in the product lifecycle. You can’t be an ivory tower architect,” he explains.

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Oshkosh puts digital solutions into overdrive

CIO Business Intelligence

Tim Scannell: Data is a major focus of most IT organizations today — collecting it from a variety of sources, transforming it into business intelligence, getting it into the hands of the right people within the organization. How extensive is your data-driven strategy today? Khare: I look at uncertainty at two tiers.

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Oshkosh puts digital solutions into overdrive

CIO Business Intelligence

Tim Scannell: Data is a major focus of most IT organizations today — collecting it from a variety of sources, transforming it into business intelligence, getting it into the hands of the right people within the organization. How extensive is your data-driven strategy today? Khare: I look at uncertainty at two tiers.

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Humans-in-the-loop forecasting: integrating data science and business planning

The Unofficial Google Data Science Blog

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. But looking through the blogosphere, some go further and posit that “platformization” of forecasting and “forecasting as a service” can turn anyone into a data scientist at the push of a button.