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My top learning and pondering moments at Splunk.conf22

Rocket-Powered Data Science

Observability is a business strategy: what you monitor, why you monitor it, what you intend to learn from it, how it will be used, and how it will contribute to business objectives and mission success. Reference ) Splunk Enterprise 9.0 Reference ) Splunk Enterprise 9.0 And the goodness doesn’t stop there.”

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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. User-friendliness: The software should be easy to use, with intuitive dashboards and user interfaces.

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

AWS Big Data

Analytics reference architecture for gaming organizations In this section, we discuss how gaming organizations can use a data hub architecture to address the analytical needs of an enterprise, which requires the same data at multiple levels of granularity and different formats, and is standardized for faster consumption.

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

AWS Big Data

This system involves the collection, processing, storage, and analysis of Internet of Things (IoT) streaming data from various vehicle devices, as well as historical operational data such as location, speed, fuel level, and component status. SOCAR is the leading Korean mobility company with strong competitiveness in car-sharing.

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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? So how is the data extracted?

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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? So how is the data extracted?

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Building Better Data Models to Unlock Next-Level Intelligence

Sisense

To support these advanced use cases, data was structured in Cloud Data Teams by Sisense (formerly Periscope Data) to simplify SQL queries on dashboards by creating varying levels of granularities in tables visible to the tool. For starters, the rise of the Internet of Things (IoT) has created immense volumes of new data to be analyzed.