Cloud-of-things analytics has a simple, powerful appeal. It offers the opportunity to know more about your business, faster. For industries ranging from retail to manufacturing, that means better operational visibility, more responsive customer service, more automated reaction to problems, and improved preventative maintenance. That’s not to mention the potential to increase revenue by launching innovative services based on new insights or event-triggered actions.
But there are challenges to moving analytics into the cloud and building a meaningful framework. Each company has different skills, capabilities, experiences, and needs when it comes to analytics. Some are highly proficient and looking to operationalize their deep learning models, while others are still introducing more contextual data sources. Here are some tips that can help companies at any stage move to the next analytics level.