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

AWS Big Data

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. Consumption This pillar consists of various consumption channels for enterprise analytical needs.

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The Future of AI in the Enterprise

Jet Global

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. But the vast reams of data generated on a daily basis are presenting a new problem for businesses—what data matters?

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The Future of AI in the Enterprise

Jet Global

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. But the vast reams of data generated on a daily basis are presenting a new problem for businesses—what data matters?

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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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How SOCAR handles large IoT data with Amazon MSK and Amazon ElastiCache for Redis

AWS Big Data

The ability to quickly measure and draw insights from data is critical in today’s business landscape, where rapid decision-making is key. With this capability, businesses can stay ahead of the curve and develop new initiatives that drive success. This is a guest blog post co-written with SangSu Park and JaeHong Ahn from SOCAR.

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My top learning moments at Splunk.conf23

Rocket-Powered Data Science

Organizations are able to monitor integrity, quality drift, performance trends, real-time demand, SLA (service level agreement) compliance metrics, and anomalous behaviors (in devices, applications, and networks) to provide timely alerting, early warnings, and other confidence measures. I call that “digital resilience for the win!