Teradata creates special IoT unit to tackle Analytics of Things

Teradata, the big data analytics and marketing applications company, has announced the creation of its Global IoT Analytics unit within Teradata Labs, based in the United States, UK and India and focused on developing innovations to derive value from Analytics of Things (AoT). The special-ops team of data scientists, data engineers and software designers are tasked with building new, cloud-based analytic solutions and services to simplify advanced analytics, data movement and database management for the Internet of Things.

“The smartest people at Teradata are laser focused on building the best technologies to power the Analytics of Things,” said Oliver Ratzesberger, president, Teradata Labs. “With this announcement, we are making it easier for our customers to move sensor data around, optimize data management systems to deal with the massive volumes of data, and run real-time, advanced analytics against streams of IoT data. We’re giving our customers powerful tools and technologies to analyze IoT data for new insights, applications and use cases.”

The company says Teradata Aster Analytics answers the “why did this happen” question using IoT data. The pre-built analytic functions include new IoT data preparation capabilities and machine learning techniques to understand and detect patterns in machine behavior. This can be used to mitigate risk, reduce maintenance cost and downtime and increase productivity.

Many of the machine learning models generated can be ported to run on virtually any operational environment that can run Java. The Teradata Aster Scoring SDK (software developer’s kit) allows analysts to deploy Aster IoT analytic models into IoT edge servers, public clouds, and in the datacenter. Teradata is also extending the IoT capabilities ofTeradata Listener with connectors that make it easier to acquire and distribute streaming sensor data for analysis.

The IoT Analytics unit is further applying machine learning and advanced analytics techniques to system administration and DevOps tasks. They are applying machine learning to Teradata systems in order to solve complex performance and workload congestion problems in seconds.

Teradata’s AoT services deliver customer solutions including early warning detection that uses predictive analytics to find and correct issues with machines and devices sooner, thus reducing repair and warranty costs while protecting brand reputation. It enables monitoring of assets to enable new revenue opportunities and pricing strategies based on power-by-the-hour and pay-per-use models instead of purchases.

It also enables real-time monitoring and analysis of physical assets, allowing companies to understand and act upon a variety of real-time insights including security alerts, energy and fuel usage, idle time, faulty parts, geo-positioning.

The new technologies and services from Teradata are available starting in the second quarter of 2016.