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Unified MLOps: Feature Stores and Model Deployment

Monte Zweben proposes a whole new approach to MLOps that allows to scale models without increasing latency by merging a database, a feature store, and machine learning.

Big Data and Analytics Services Market To Leverage Continuous Intelligence For Improved Decision-Making

Machine learning data pipeline outfit Splice Machine files for insolvency

Machine learning data pipeline outfit Splice Machine files for insolvency
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How IoT s Massive Data Sprawl Opens New Opportunities

How IoT’s ‘Massive Data Sprawl’ Opens New Opportunities The growth of the Internet of Things market means an incoming, perpetually expanding flood of data, which creates all sorts of big new problems that can translate into big new opportunities for solution providers. CRN talks to executives at three vendors working in IoT, edge computing and AI about the different kinds of software and systems that can help organizations make sense out of all the IoT data they’re collecting. By Dylan Martin July 26, 2021, 05:51 PM EDT There is a data tsunami coming and well, it may already be here, largely thanks to the increasingly growing number of IoT sensors and endpoints that are sprouting at the edge. Consider Gartner’s prediction from a few years ago that the amount of data created by enterprises outside traditional data centers will reach 75 percent, much higher than the 10 percent figure it assessed for 2018.

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