The Internet of Things (IoT) describes devices with sensors and computational ability which let them collect, exchange, and act on data. IoT is a broad category that includes uses from smart home thermostats to industrial manufacturing equipment. Sensor data is time series data, and IoT is a common use case for InfluxDB because it can handle the huge amounts of data IoT sensors create.

Cloud spend — which research shows makes up 51% of IT budgets — is a prime candidate for company cost savings initiatives with the potential to make a huge difference in gross margins. It’s also an area that has grown dramatically in the last few years due to digital transformation and a rise in cloud demand during the pandemic.

This article was originally published in The New Stack and is reposted here with permission. Hundreds of billions of sensors produce vast amounts of time series data every day. The sheer volume of data that companies collect makes it challenging to analyze and glean insights. Machine learning drastically accelerates time series data analysis so that companies can understand and act on their time series data to drive significant innovation and improvements.

Learn how to deploy InfluxDB Cloud’s Native Collectors with Kepware and The Things Network. Did you hear about the new feature that just dropped to InfluxDB Cloud? Native Collectors! Starting with MQTT. There will be plenty of content to get you started with Native Collectors. So this blog series covers connecting two popular IoT-based platforms to InfluxDB Cloud using native Collectors. One Enterprise use case and one industrial use case.