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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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5 Key Takeaways from #Current2023

Cloudera

As organizations shift from the modernization of data-driven applications via Kafka towards delivering real-time insight and/or powering smart automated systems, Flink At Current, adoption of Flink was a hot topic and many of the vendors (Cloudera included) use Flink as the engine to power their stream processing offerings as well.

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3 Takeaways from Gartner’s 2018 Data and Analytics Summit

DataRobot Blog

Today, data integration is moving closer to the edges – to the business people and to where the data actually exists – the Internet of Things (IoT) and the Cloud. 4 Data and analytics leaders, CDOs, and executives will increasingly work together to develop creative ways for data assets to generate new revenue streams.

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Building Better Data Models to Unlock Next-Level Intelligence

Sisense

The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021!

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The Data Behind Tokyo 2020: The Evolution of the Olympic Games

Sisense

From an operational data analytics perspective, I would describe Tokyo 2020 as a coming of age Games,” he says. Data will create a better-connected future. We want to serve these different needs as effectively as possible.”. Chris’ passion around this is evident. I’m really quite excited about what can be achieved.”.