When it comes to the IoT (Internet of Things), the conversation may start in any number of places, but it always comes back to the data and how it can be used. Whether a city is collecting environmental sensor data from connected streetlights or a manufacturer is collecting usage information and diagnostics from “smart” machines on the factory floor, the key question is always: What insights can the business gain from this data? Similarly, what actions can the business take as a result of these insights?
McKinsey & Co., www.mckinsey.com, projects that data from IoT-connected devices will produce insights that drive a potential economic value of $11 trillion by 2025. What McKinsey doesn’t predict is that the data itself will generate $11 trillion by 2025. Rather, it’s the insights derived from IoT data that will provide this projected push in economic value. While the IoT is becoming more of a common conversation in many enterprise circles, not all businesses have maximized the benefits available to them via advanced IoT data analytics.
This will inevitably change as the market matures. The latest “Worldwide Semiannual Big Data and Analytics Spending Guide” from IDC (Intl. Data Corp.), www.idc.com, reports worldwide revenues for Big Data and business analytics will grow from about $130 billion in 2016 to more than $203 billion in 2020. Dan Vesset, IDC’s group vice president of analytics and information management, said in response to the report that “the availability of data, a new generation of technology, and a cultural shift toward data-driven decisionmaking continue to drive demand for Big Data and analytics technology and services.”
Further, the continuing advancement of AI (artificial intelligence) and machine learning will also drive demand for Big Data and analytics technology and services. Companies like AT&T, www.att.com, which provide IoT connectivity and related services to enterprise customers, are recognizing that businesses want not only fast network speeds that deliver data quickly and reliably, but also the ability to extract meaningful analysis from this data—and an AI/machine learning-enabled platform like IBM Watson could be the answer.
Expanding on an existing partnership, AT&T and IBM, www.ibm.com, recently unveiled a pilot collaboration that aims to help enterprise customers transform industrial IoT data into realtime analytic insights. These insights could open doors to strategic, data-driven actions that can improve business operations. IBM Watson on the Cloud powers the new AT&T IoT analytics solution, which combines AT&T IoT solutions like AT&T M2X, Flow Designer, and Control Center with IBM Watson’s IoT portfolio, including the IBM Watson Data Platform and IBM Machine Learning Service.
By integrating IBM Watson technology, AT&T is extending enterprise customers’ ability to connect, build, launch, and manage IoT apps and devices. It’s also extending customers’ ability to uncover business insights via IBM’s data ingestion engine with cognitive-powered decisionmaking and machine learning. One of the most important value adds customers will gain from the collaboration is predictive maintenance capabilities.
As the demand for realtime or near-realtime data and analytics grows, carriers and other connectivity providers will need to look for ways to keep up with the evolving needs of their customers. Machine learning-enabled data analytics that allow enterprises to make mission-critical decisions when they’re needed most will go a long way in doing so.
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