Four Steps to Unlocking Cost-Effective Business Insights from IoT Data

Formalizing a cloud strategy can help you reach the point of readiness regarding business intelligence and the Internet of Things.
By Peter Shashkin
Feb 01, 2017

Smart homes, cars and cities—the Internet of Things has become increasingly democratized. But what does the IoT mean for the enterprise? According to a report by Verizon, 72 percent of organizations believe that the IoT brings competitive advantages. That sentiment is reflected by a separate report from BI Intelligence, predicting that the enterprise sector will account for almost 40 percent of active IoT devices by 2019.

But with a surge in connected devices, enterprises can expect their data glut to become a lot bigger. To competitively harness the potential of any IoT strategy, enterprises must find cost-effective and scalable ways to unlock value from IoT-derived big data.

Data, after all, is only as good as its application. Thanks to the application of advanced analytics, it has now become a powerful business tool.

Big data has strategic benefits for any enterprise across an infinite number of uses cases. When IoT-gathered data is parsed and visualized via real-time dashboards, any business user can make data work strategically for them to get a better perspective on operational trends, system performance, cost management, location-driven insights and more. The IoT is fast becoming an enabler of sophisticated business intelligence (BI).

The possibilities are endless. The problem for the enterprise is that many organizations jump in without considering how they will manage and analyze the data they amass. Enter cloud computing.

Powering IoT-Driven Insights via the Cloud
It's no coincidence that cloud computing and big data have evolved in parallel. The cloud is the ideal platform for processing data, and has made BI accessible to enterprises of all sizes.

Powered by the cloud, organizations can achieve unparalleled time to value for BI initiatives. With capabilities such as data ingestion, data transformation, machine learning, stream analytics and storage at scale, cloud BI levels the playing field. It's cheaper and easier to manage than on-premises systems and doesn't require vast IT headcount or data scientists to administer. Users also get features that were previously unavailable to them: dashboard KPIs, ease-of-use, anytime/anywhere access (on or off site, via a browser or mobile device)—cloud BI tools provide a window to all of it.

The cloud also introduces data transparency to the IoT. By exposing and sharing gathered data via cloud-based application programming interfaces (APIs), enterprises can share and extend the value of data with other stakeholders—partners, employees, customers and external developers.

But how do you formalize a cloud strategy that gets you to the point of IoT and BI readiness? We recommend the following four-step approach to successfully deploying a cloud-enabled IoT BI strategy.

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