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

By Peter Shashkin

Formalizing a cloud strategy can help you reach the point of readiness regarding business intelligence and the Internet of Things.

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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.

Step One: Collect Good Data
Quality data is essential to any BI strategy. If that data lacks integrity, it can impact everything downstream (report quality, etc.). Focus on devices that produce minimal noise. Existing technologies like smartphones and smart apps will often do the job, since they transmit data seamlessly to the cloud, bypassing the need for costly hardware investments.

Step Two: Process Data and Create Reports
Once data is gathered, BI can begin to be gleaned. Using processing tools, data anomalies can be detected, problems identified and insights uncovered. This process can be performed by standalone out-of-the-box cloud BI tools or via a more customized process. For example, if you’re looking to manipulate real-time data, send alerts, process aggregations, integrate data with existing systems and leverage web-based insights (particularly geospatial and map-based visualizations), more custom development may be required.

Step Three: Share Your Data
This is where APIs come into play. APIs are powerful tools that let you expose your data to application development communities who know how to harness the power of that data through applications, thereby driving more value-creation opportunities. This displaces the traditional process of hiring a team of application developers to help you put your data to use, and removes barriers between business units, while inviting attention from partners, customers, software developers and so forth.

Step Four: Be Open to Feedback
With openness comes feedback. Invite input from those who use your data services (API users) and adjust accordingly. Perhaps the developer community notices problems with your data, or finds new ways to bring additional value to your datasets. It’s a valuable way to successfully deploy a cloud-enabled, IoT business intelligence strategy mindset and outcome that is often alien to an enterprise culture where everything is siloed, and data becomes stale and under-utilized, and quickly loses its value.

The Future Is Here
The Internet of Things isn’t just rapidly reshaping the way we do business today—it’s also opening new opportunities that have yet to be discovered. The imperative, capabilities and tools exist today to successfully deploy a cloud-enabled, IoT business intelligence strategy. Is your enterprise ready?

A veteran of EastBanc Technologies, Peter Shashkin is an accomplished enterprise architect, project management professional, Scrum Master and real-life rocket scientist. Having helped the company achieve Microsoft Partner Gold Application Development and Gold Collaboration and Content partner status, Peter is EastBanc’s go-to technology lead for SharePoint, Dynamics CRM, Azure and other Microsoft deployments. Peter is skilled at knowing how to transform technology into a differentiator, and is passionate about harnessing the power and convergence of the cloud, mobile technology and the IoT to support customers’ strategic goals. He graduated from Novosibirsk State University with a Master’s degree in applied mathematics, and lives in Bethesda, Md., with his wife and daughter.