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The Essential Guide to Machine Learning on the Stream

A deep dive into how streaming processing and streaming analytics helps organizations get faster results and more value from data
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The modern economy is digitized. With this transformation comes troves of data of all types and sizes. While many organizations are looking to leverage these new data streams, a Splunk report found that more than 55% of organizations think that the volume of data is growing faster than they can keep up with. The solution lies with streaming machine learning, which does not require a lot of resources, time or expense to train as data volume and cardinality increase

Download The Essential Guide to Machine Learning on the Stream and understand:

  • How streaming data poses challenges due to its volume, variety and velocity, while also providing immense opportunity
  • How streaming machine learning overcomes the challenges of traditional batch models and delivers real-time outcomes
  • How Splunk’s streaming ML provides a framework of machine learning models and pipelines that are optimized for streaming data analytics

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