Teradata introduces IoT analytics accelerators

Organisations should develop plans to ensure that data is optimised to deliver compelling ROI

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Teradata introduces IoT analytics accelerators Ratzesberger: Our AoTAs seen to overall equipment effectiveness, while improving predictability and asset availability.
By  David Ndichu Published  October 3, 2016

Analytics solutions firm Teradata has announced four new accelerators designed to speed up the transformation of Internet of Things (IoT) data to actionable insight.

Teradata “Analytics of Things Accelerators” (AoTAs) are derived from field engagements at global IoT companies in manufacturing, transportation, mining, energy and utilities, the company says. The accelerators are comprised of technology-agnostic intellectual property (IP) and professional services, it added.

Teradata AoTAs help organisations determine what sensor data to trust and keep, while choosing types and combinations of analytical techniques to best address specific business questions. The accelerators help organisations move from costly experimental projects to enterprise-class solutions scaling across thousands of connected devices and assets. Specifically, the new Teradata AoTAs include:

1) Condition-Based Maintenance Accelerator, which continuously monitors and analyses asset data from remote devices or equipment at scale to increase availability, improve safety, and reduce costs;

2) Manufacturing Performance Optimisation Accelerator, which identifies complex production problems across equipment performance and availability for quick corrective action;

3) Sensor Data Qualification Accelerator, which automates recommendations on the optimal frequency of sensor readings based on relevant anomaly patterns;

4) Visual Anomaly Prospector Accelerator, which mines large amounts of multidimensional time series (MTS) data from remotely monitored equipment and devices, and visually helps an end user discover anomaly patterns that frequently precede a key event. 

"To improve Caterpillar’s customers’ total cost of ownership, we now have in place engine sensor feeds that show where and when remote engines need intervention, and we can predict failures across the fleet, which allows for forecasting replacement part inventory needs and recommending proactive maintenance tasks,” said Scott Ulrich, senior engineering team leader, large power systems division, Caterpillar.

“Teradata AoTAs are already addressing and resolving $100 million-dollar problems for manufacturers of vehicles, equipment, oil and gas systems, and consumer goods,” said Oliver Ratzesberger, executive vice president and chief product officer, Teradata. “These challenges represent billion-dollar budgets for each company, to be clear on the scale of business value addressed by AoTA. For example, our AoTAs have increased overall equipment effectiveness as much as 85 percent, while also improving predictability and asset availability.”

Forecasts project 21 billion connected "things" in the digital universe by 2020. With data volumes generated by the IoT already dwarfing data waves from social media, information leaders must begin now to identify the requirements necessary to support adoption and implementation of IoT capabilities. Along with establishing requirements, they must also develop strategies, processes and execution plans to ensure that data is optimised to deliver compelling ROI.

“Teradata consulting professionals are veterans at solving the biggest data problems in virtually every major industry, and experts in the use of IoT data, regardless of the customer’s analytic ecosystem,” Ratzesberger said.

Teradata “Analytics of Things Accelerators” are available immediately.

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