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
The Essential Guide to Machine Learning on the Stream
