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Streamlining supply chain management: Strategies for the future

IBM Big Data Hub

Big data and predictive analytics are increasingly being used to improve forecasting accuracy, allowing businesses to respond more effectively to changes in customer needs. Real-time tracking systems, often enabled by Internet of Things (IoT) devices, help companies monitor their supply chain accurately and immediately.

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How Data Analytics Is Changing The Insurance Industry

Smart Data Collective

The insurance industry is based on the idea of managing risk. To determine this risk, the industry must consult data and see what trends are evident to draft their risk profiles. The in-depth analysis of historical data gives insurers a platform to base their determination of risk.

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Six EAM trends pushing the oil and gas industries forward

IBM Big Data Hub

EAM systems can include functions like maintenance management, asset lifecycle management , inventory management and work order management, among others. Predictive and preventive maintenance : The advent of IoT and AI technologies has transformed EAM systems into predictive maintenance tools.

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How to Manage Risk with Modern Data Architectures

Cloudera

Implementing a modern data architecture makes it possible for financial institutions to break down legacy data silos, simplifying data management, governance, and integration — and driving down costs. Apply emerging technology to intraday liquidity management. Enhance counterparty risk assessment.

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Incorporating Artificial Intelligence for Businesses : The Modern Approach to Data Analytics

BizAcuity

Not just banking and financial services, but many organizations use big data and AI to forecast revenue, exchange rates, cryptocurrencies and certain macroeconomic variables for hedging purposes and risk management. Integrating IoT and route optimization are two other important places that use AI. AI in Healthcare.

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Interview with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity

Corinium

And more recently, we have also seen innovation with IOT (Internet Of Things). Machine learning can keep up, by continually looking for trends and anomalies, or predictive analytics, that are interesting for the given use case. You can protect individual fields, or even subsets of fields (e.g.

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Big Data Fabric Weaves Together Automation, Scalability, and Intelligence

Cloudera

It enables orchestration of data flow and curation of data across various big data platforms (such as data lakes, Hadoop, and NoSQL) to support a single version of the truth, customer personalization, and advanced big data analytics. Cloudera Enterprise Platform as Big Data Fabric. Flexible/Location-agnostic Infrastructure.