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Six EAM trends pushing the oil and gas industries forward

IBM Big Data Hub

More recently, these systems have integrated advanced technologies like Internet of Things (IoT), artificial intelligence (AI) and machine learning (ML) to enable predictive analytics and real-time monitoring. Trend #5: The rise of mobile EAM solutions Mobile technology is making EAM more accessible than ever.

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

AWS Big Data

ETL (extract, transform, and load) technologies, streaming services, APIs, and data exchange interfaces are the core components of this pillar. Unlike ingestion processes, data can be transformed as per business rules before loading. However, it’s not mandatory to use the same technologies.

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The Future of AI in the Enterprise

Jet Global

The business world is at an inflection point when it comes to the application of Artificial Intelligence (or AI). Thankfully, with the widespread adoption of cloud computing and the Internet of Things, data has never been more readily available in today’s business world. Read: The Enterprise AI Revolution Starts with BI.

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The Future of AI in the Enterprise

Jet Global

The business world is at an inflection point when it comes to the application of Artificial Intelligence (or AI). Thankfully, with the widespread adoption of cloud computing and the Internet of Things, data has never been more readily available in today’s business world. Read: The Enterprise AI Revolution Starts with BI.

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12 considerations when choosing MES software

IBM Big Data Hub

Gathering data from machines, sensors, operators and other Industrial Internet of Things (IIoT) devices, they provide accurate and up-to-date insights into the status of production activities. They also support the measurement of overall equipment effectiveness (OEE) , a significant metric used to gauge manufacturing efficiency.

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Top 10 Data Innovation Trends During 2020

Rocket-Powered Data Science

These data-fueled innovations come in the form of new algorithms, new technologies, new applications, new concepts, and even some “old things made new again”. This steady march of data-driven innovation has been a consistent characteristic of each year for at least the past decade. And the goodness doesn’t stop there.

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Building Better Data Models to Unlock Next-Level Intelligence

Sisense

Both of these concepts resonated with our team and our objectives, and so we found ourselves supporting both to some extent. It often will collapse the metrics in a fact table to the level of a single dimension through a form of aggregation or lookback window.