Remove Data Quality Remove IoT Remove Metadata
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Data Governance and Metadata Management: You Can’t Have One Without the Other

erwin

When an organization’s data governance and metadata management programs work in harmony, then everything is easier. Data governance is a complex but critical practice. There’s always more data to handle, much of it unstructured; more data sources, like IoT, more points of integration, and more regulatory compliance requirements.

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

Their terminal operations rely heavily on seamless data flows and the management of vast volumes of data. Recently, EUROGATE has developed a digital twin for its container terminal Hamburg (CTH), generating millions of data points every second from Internet of Things (IoT)devices attached to its container handling equipment (CHE).

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Top 10 Data Governance Trends for 2020: Data’s Real Value Comes Into Focus

erwin

To that end, data is finally no longer just an IT issue. As organizations become data-driven and awash in an overwhelming amount of data from multiple data sources (AI, IoT, ML, etc.), they will find new ways to get a handle on data quality and focus on data management processes and best practices.

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Are Data Governance Bottlenecks Holding You Back?

erwin

While acknowledging that data governance is about more than risk management and regulatory compliance may indicate that companies are more confident in their data, the data governance practice is nonetheless growing in complexity because of more: Data to handle, much of it unstructured. Sources, like IoT.

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How HPE Aruba Supply Chain optimized cost and performance by migrating to an AWS modern data architecture

AWS Big Data

Aruba offers networking hardware like access points, switches, routers, software, security devices, and Internet of Things (IoT) products. This complex process involves suppliers, logistics, quality control, and delivery. Each file arrives as a pair with a tail metadata file in CSV format containing the size and name of the file.

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Embedding AI Into Every Aspect of Your Business

Cloudera

robots), AR/VR in manufacturing (quality), power grid management, automated retail, IoT, Intelligent call centers – all powered by AI – the list of potential use cases is virtually endless. . Build your data strategy around relevant data, not last years data because it’s easy to access.

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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

Sources Data can be loaded from multiple sources, such as systems of record, data generated from applications, operational data stores, enterprise-wide reference data and metadata, data from vendors and partners, machine-generated data, social sources, and web sources.