Shining The Light On Dark Data

Paul Dennies, Global Program Director, Teradata
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Paul Dennies, Global Program Director, Teradata

Data and analytics will form the foundation of factories of the future and in so doing will provide manufacturers previously unimaginable levels of business resiliency, productivity and product and service innovation. Companies that embrace the use of data and analytics will be positioned to meet ever-changing market demands. Those that do not will almost inevitably lose customers and profitability and will face the financial and continuity risks associated with competitive disadvantage.

Driving this change are the advances in technology that enable increased functionality of manufactured products. This subsequently boosts the complexity of manufacturing processes as well as the equipment used to support those processes. In turn, the complexity of the machinery and processes dramatically increases the amount of data generated and collected by manufacturers.

All of this creates an upward spiral – more sophisticated manufacturing processes leads to more sophisticated products that leads to more data that can be used to create more sophisticated processes and products.

A broad range of products generate data, ranging from manufacturing equipment, to magnetic resonance imaging machines, to mobile devices, to software. This data is referred as “dark” data because it is usually excluded from existing IT systems and processes. Manufacturers the world over are seeking ways to analyze this dark data and use the results to guide and improve their operations. Whether it is data produced by a piece of manufacturing equipment, by an asset deployed in the field, or collected from their website, manufacturers are looking for cost-effective analytic algorithms to identify patterns, enhance insights, and ultimately improve decisions based on dark data.

High-tech manufacturers possess large amounts of this dark data. For instance, leading high-tech manufacturers are using sensor, telematic, click-stream, and social media data to help with:
• Manufacturing. By analyzing sensor data, manufacturing firms can tell if equipment becomes misaligned or begins to malfunction before problems erupt that can cause production delays or increase costs.
• Field services. Products “call home” and send operational data that can be analyzed to allow manufacturers to contact customers and offer servicing prior to failure or malfunction.
• Digital m arketing. Leading manufacturers are gathering cross-channel insights that come from multiple sources— product sensors, website activity, and customer purchases—to generate 360-degree views of the customer.

Sixty-one percent of respondents to a Gartner survey said that dark data represented their most immediate opportunity to leverage big data.

Short product lifecycles, fierce competition, and regulatory compliance mandates have forced high-tech manufacturers to rethink how they can use dark data. Architectures that support the integration and analytics of structured and unstructured data allow them transparent access to all their data, enabling them to boost productivity, reduce costs, and seize new competitive advantage.

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