HAMBURG, Germany -- Teradata opens its Global IoT Analytics unit within Teradata Labs, based in the United States, UK and India, and focused on developing innovations to derive the greatest value from the 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.
Teradata Aster Analytics: Anytime, Anywhere
Teradata Aster Analytics answers the powerful "why did this happen" question using IoT data. The pre-built analytic functions include new IoT data preparation capabilities and machine learning techniques to quickly understand and detect patterns in machine behavior. This can be used to mitigate risk, reduce maintenance cost and downtime and increase productivity. Aster Analytics makes it easier and faster to find meaningful and relevant insights hidden in massive volumes of IoT data with millisecond performance.
Many of the machine learning models generated can be easily ported to run on virtually any operational environment that can run Java. The Teradata Aster Scoring SDK (software developer's kit) allows analysts to easily deploy Aster IoT analytic models into virtually any IoT edge servers, public clouds, and in the data center.
Faster Collection and Distribution of IoT Data Streams from Teradata Listener Enhancements
Teradata is extending the IoT capabilities of Teradata Listener with connectors that make it easier to acquire and distribute streaming sensor data for analysis. Capturing and managing continuous streams of data is normally complex and labor intensive. These new connectivity options make it easy and fast for Listener to deliver new data streams of sensor data to the Teradata Unified Data Architecture, either on-premises and in the cloud.
A Global IoT Analytics Unit
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 countless 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.
•Continuous 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.
•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 and more.
The new technologies and services from Teradata are available starting in the second quarter of 2016.
For more details, visit http://www.teradata.com