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Mastering healthcare data governance with data lineage

IBM Big Data Hub

The healthcare industry faces arguably the highest stakes when it comes to data governance. The impact of healthcare data usage on people’s lives lies at the heart of why data governance in healthcare is so crucial.In healthcare, managing the accuracy, quality and integrity of data is the focus of data governance.

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Renewable energy in action: Examples and use cases for fueling the future

IBM Big Data Hub

Here, we will look at examples and applications of renewable energy across a variety of industries, its impact on energy systems and the energy technologies that will drive its use in the future. Through AI, IoT and analytics, this cloud-based platform can optimize performance and reduce operational costs. trillion in 2023.

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Connected products at the edge

IBM Big Data Hub

This is especially true in manufacturing and industrial engineering. which involves the integration of advanced digital technologies and IoT into manufacturing processes and connected devices that transmit and receive instructions and data. Smart components (phones, tablets, sensors, microprocessors and analytics).

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4 strategic sourcing use cases to strengthen your supply chain

IBM Big Data Hub

Such analysis and decision-making are often optimized with the help of various technologies, including artificial intelligence tools and data analytics platforms. For example, Antonello Produce wanted to provide food that its customers could trust. 3 Building a viable and sustainable ecosystem of partners is complex.

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Top 10 Governance, Risk and Compliance (GRC) Vendors

eSecurity Planet

Governance, risk, and compliance (GRC) software helps businesses manage all of the necessary documentation and processes for ensuring maximum productivity and preparedness. Third-party governance. IT governance and security. Privacy governance and management. Enterprise & operational risk management. Audit management.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. For example, is the problem related to declining revenue or production bottlenecks? A manufacturer developed powerful, 3D-printed sensors to guide driverless vehicles.

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5 misconceptions about cloud data warehouses

IBM Big Data Hub

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. This enabled data-driven analytics at scale across the organization 4.

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