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Achieving Trusted AI in Manufacturing

Cloudera

According to Gartner , 80 percent of manufacturing CEOs are increasing investments in digital technologies—led by artificial intelligence (AI), Internet of Things (IoT), data, and analytics. Manufacturers now have unprecedented capacity to collect, utilize, and manage massive amounts of data.

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P&G turns to AI to create digital manufacturing of the future

CIO Business Intelligence

The partners say they will create the future of digital manufacturing by leveraging the industrial internet of things (IIoT), digital twin , data, and AI to bring products to consumers faster and increase customer satisfaction, all while improving productivity and reducing costs. Smart manufacturing at scale.

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Keys to Ensure that Data isn’t Slowing Down your Innovation Efforts

Cloudera

For those models to produce meaningful outcomes, organizations need a well-defined data lifecycle management process that addresses the complexities of capturing, analyzing, and acting on data. In modern hybrid environments, data traverses clouds, on-premise infrastructure and IoT networks, so the process can get very complex.

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

AWS Big Data

A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and data lakes can coexist in an organization, complementing each other.

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Big Data Fabric Weaves Together Automation, Scalability, and Intelligence

Cloudera

Forrester describes Big Data Fabric as, “A unified, trusted, and comprehensive view of business data produced by orchestrating data sources automatically, intelligently, and securely, then preparing and processing them in big data platforms such as Hadoop and Apache Spark, data lakes, in-memory, and NoSQL.”.

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The Energy Utilities Series: Challenges and Opportunities of Decarbonization (Post 2 of 6)

Data Virtualization

The post The Energy Utilities Series: Challenges and Opportunities of Decarbonization (Post 2 of 6) appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information. Decarbonization is the process of transitioning from.

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It’s not your data. It’s how you use it. Unlock the power of data & build foundations of a data driven organisation

CIO Business Intelligence

However, more than 99 percent of respondents said they would migrate data to the cloud over the next two years. The Internet of Things (IoT) is a huge contributor of data to this growing volume, iotaComm estimates there are 35 billion IoT devices worldwide and that in 2025 all IoT devices combined will generate 79.4