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Using Artificial Intelligence to Make Sense of IoT Data

BizAcuity

IoT is basically an exchange of data or information in a connected or interconnected environment. As IoT devices generate large volumes of data, AI is functionally necessary to make sense of this data. Data is only useful when it is actionable for which it needs to be supplemented with context and creativity.

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Apache Iceberg optimization: Solving the small files problem in Amazon EMR

AWS Big Data

In our previous post Improve operational efficiencies of Apache Iceberg tables built on Amazon S3 data lakes , we discussed how you can implement solutions to improve operational efficiencies of your Amazon Simple Storage Service (Amazon S3) data lake that is using the Apache Iceberg open table format and running on the Amazon EMR big data platform.

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DS Smith sets a single-cloud agenda for sustainability

CIO Business Intelligence

The migration, still in its early stages, is being designed to benefit from the learned efficiencies, proven sustainability strategies, and advances in data and analytics on the AWS platform over the past decade. This enables the company to extract additional value from the data through real-time availability and contextualization.

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Snowflake: Data Ingestion Using Snowpipe and AWS Glue

BizAcuity

This typically requires a data warehouse for analytics needs that is able to ingest and handle real time data of huge volumes. Snowflake is a cloud-native platform that eliminates the need for separate data warehouses, data lakes, and data marts allowing secure data sharing across the organization.

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Achieving Trusted AI in Manufacturing

Cloudera

But with this data — along with some context about the business and process — manufacturers can leverage AI as a key building block to develop and enhance operations. There are many functional areas within manufacturing where manufacturers will see AI’s massive benefits. Eliminate data silos. That is a very low number.

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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. The power of people.

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When will AI usher in a new era of manufacturing?

CIO Business Intelligence

However, some things are common to virtually all types of manufacturing: expensive equipment and trained human operators are always required, and both the machinery and the people need to be deployed in an optimal manner to keep costs down. Moreover, lowering costs is not the only way manufacturers gain a competitive advantage.