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7 famous analytics and AI disasters

CIO Business Intelligence

Organizations across every industry have been and continue to invest heavily in data and analytics. But like oil, data and analytics have their dark side. Here are a handful of high-profile analytics and AI blunders from the past decade to illustrate what can go wrong. Target analytics violated privacy.

Analytics 141
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Minimizing Supply Chain Disruptions with Advanced Analytics

Cloudera

Advanced analytics empower risk reduction . Advanced analytics and enterprise data are empowering several overarching initiatives in supply chain risk reduction – improved visibility and transparency into all aspects of the supply chain balanced with data governance and security. .

Analytics 109
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Improve healthcare services through patient 360: A zero-ETL approach to enable near real-time data analytics

AWS Big Data

Achieving this will also improve general public health through better and more timely interventions, identify health risks through predictive analytics, and accelerate the research and development process. This will be your online transaction processing (OLTP) data store for transactional data.

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Buy Your Embedded Analytics and Empower Your End-Users With the Right Data

Jet Global

The value of embedded analytics is unmistakable. These costs are not always visible when companies plan for their analytics offering but can significantly impact production, scale, and the speed of bringing analytics to market. The challenge is collecting all that data into one place and making it understandable.

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10 Examples of How Big Data in Logistics Can Transform The Supply Chain

datapine

Table of Contents 1) Benefits Of Big Data In Logistics 2) 10 Big Data In Logistics Use Cases Big data is revolutionizing many fields of business, and logistics analytics is no exception. The complex and ever-evolving nature of logistics makes it an essential use case for big data applications.

Big Data 275
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Big Data Analytics Is The 21st Century’s Biggest Disruptor In Healthcare

Smart Data Collective

The healthcare sector is heavily dependent on advances in big data. Healthcare organizations are using predictive analytics , machine learning, and AI to improve patient outcomes, yield more accurate diagnoses and find more cost-effective operating models. Big data analytics: solutions to the industry challenges.

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Digital twin helps NTT Indycar deliver better race experience to fans

CIO Business Intelligence

When Marcus Ericsson, driving for Chip Ganassi Racing, won the Indianapolis 500 in May, it was in a car equipped with more than 140 sensors streaming data and predictive analytic insights, not only to the racing team but to fans at the Brickyard and around the world. That’s where the data and analytics come in.