Remove Analytics Remove Big data Remove Insurance Remove Unstructured data
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How IBM and AWS are partnering to deliver the promise of AI for business

IBM Big Data Hub

IBM, a pioneer in data analytics and AI, offers watsonx.data, among other technologies, that makes possible to seamlessly access and ingest massive sets of structured and unstructured data. A leading insurance player in Japan leverages this technology to infuse AI into their operations.

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5 misconceptions about cloud data warehouses

IBM Big Data Hub

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

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The most valuable AI use cases for business

IBM Big Data Hub

By infusing AI into IT operations , companies can harness the considerable power of NLP, big data, and ML models to automate and streamline operational workflows, and monitor event correlation and causality determination. Maintenance schedules can use AI-powered predictive analytics to create greater efficiencies.

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Data governance use cases – 3 ways to implement

Collibra

Data lake management: Prevent a data swamp. A data lake is a storage repository that holds a vast amount of raw data in its native format, including structured, semi-structured and unstructured data. The data structure and requirements are not defined until the data is needed.

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4 ways insurers can improve data veracity

Information Management Resources

Managing this crucial component of data management will help carriers get better results from their analytics, AI and blockchain initiatives.

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Reducing administrative burden in the healthcare industry with AI and interoperability

IBM Big Data Hub

The rule laid out an interoperability journey that supports seamless data exchange between payers and providers alike — enabling future functionalities and technically incremental use cases. These requirements enable the exchange of important data between healthcare payers and providers.

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Measure Twice, Cut Once: How the Right Data Modeling Tool Drives Business Value

erwin

Additional challenges, such as increasing regulatory pressures – from the General Data Protection Regulation (GDPR) to the Health Insurance Privacy and Portability Act (HIPPA) – and growing stores of unstructured data also underscore the increasing importance of a data modeling tool.