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Comparing Vitria OI with Other Analytics Solutions All companies search for insights from the data they generate, and most have invested in Business Intelligence (BI) solutions from large software vendors. These products provide historical analysis for medium- to long-term planning—essential activities for any business. However, these products are always looking in the rear-view mirror. As you look for ways to reduce or eliminate the latency…
…on customer profiles You’ll know your customers’ habits, their usage patterns and any previous issues. With this information you’ll be able to offer new products, services or enhancements that are personalized. Over the long term, this can help you transition your own image from “utility” to partner. A Closer Look At IoT Analytics IoT analytics come in all shapes and sizes, as today’s utilities know well. But beyond the fog of vendor claims,…
…maly detection – Once the parts are visible, analytics can find patterns of anomalies, even when they encompass multiple machines, processes, or levels of operation within processes; Change management – The next step is to determine what processes, or customers, for instance, may be affected by these anomalies. Change management analytics can be used to identify target populations so they can be serviced proactively, in some cases before, rather…
…d of the IoT value chain are business and consumer customers, enjoying an ever-widening array of competitive product choices and features. Telecoms need to make customer marketing a priority, and they know it. That’s why a research report by Tata Consultancy Services found that telecom spending on customers – on product monitoring, tracking, services and related initiatives – has outpaced telecom supply chain spending by about four to one. How…
…success will come by keeping a strong focus on customers and customer service, since it’s customers who, ultimately, pay the bills. In that spirit, here’s what to look for in your own IoT analytics team: Data Scientists The term “data scientist” actually covers a range of skills, and even nomenclatures, including data engineer and machine-learning engineer. New skills seem to be added daily because of the fast-evolving nature of analytics…
…ns of suppliers and customers, as well as multifaceted production and operational structures. The potential for gaining insight from IoT analysis is everywhere and anywhere at any given time. It’s up to the manufacturer to determine where, when and how best to make the necessary capital investment. If you’re like most, you’re already using machine sensors to help with service diagnostics in production machinery and field equipment. You’re also…
…vices are deployed in the cloud; others come directly from third parties. Also, large network segments are virtualized, thus reducing direct visibility into network components and making it difficult to detect problems and determine which services – and customers – are being affected. Prior Learning Helps To do its job, automated incident management makes use of information gleaned from anomaly detection, which finds anomaly patterns over time,…
…r can only store the records for the past two weeks. After that it overwrites the old records with fresh logs. The cost of storing and maintaining the data on-premises is hard to justify. This leaves the company with a short-term memory problem. A better solution would be to move the analytics and storage into the cloud. There economies of scale are far greater and cost per gigabyte of storage plummets, making data more viable to retain. Now the…
…y, and with little impact on current operations, by following Vitria’s “Quick Start” M3O Operations Book methodology. Vitria’s Professional Services facilitated an iterative design process to develop the operational views, determine the required information, and get information easily from the underlying systems. In these economic times when budgets are tight, a combination of short-term benefits with a repeatable methodology proved to be a…
…plement BPM and Analytics projects quickly and efficiently. As the Sprint teams deploy, the COE is at the ready to provide training, reusable assets, and general knowledge. The COE can also serve as the first line of support in case any issues arise during or after the implementation. Finally, and perhaps most importantly, the COE facilitates a consistent and complete knowledge transfer to the customer teams to ensure long-term self sufficiency….
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A Flexible IoT Analytics Framework - How Digital Operations Analytics Will Predict The Future
- Telecoms: Unlock The IoT Value Chain To Optimize Digital Transformation
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