Teradata presented a task force composed of data scientists and software designers to simplify the analysis of the Internet of Things.
Teradata, yesterday announced the creation, within Teradata Labs, of the Global IoT Analytics, a task force that focuses on the development of innovations to get the most value possible from the AO (Analytics of Things). The data scientists, data engineers and designers software that are part of the task force in charge of designing new analytic solutions and services cloud to simplify advanced analysis, data transfer and management of databases for the Internet of things.
“With this announcement, we make it easier for our customers to manage sensor-generated data, optimize data management systems to cope with their huge volumes and perform advanced analysis on IoT data streams in real time. We are giving our customers powerful tools and technologies to analyze IoT data and get new information and develop new applications and use cases, ” said Oliver Ratzesberger, president of Teradata Labs.
Among the various solutions put in place for this purpose stands Teradata Aster Analytics, which is able to answer the question “why it happened” thanks to the use of IoT data. The solution developed by Teradata has integrated analytical functions such as the ability to organize IoT data and learning techniques for a quick understanding and identification of patterns in machine behavior.
THE IOT ANALYTICS UNIT IS APPLYING ADVANCED MACHINE LEARNING AND ANALYSIS TECHNIQUES TO DEVOPS ACTIVITIES
Aster Analytics simplifies and accelerates the detection of relevant information hidden in huge volumes of IoT data, ensuring performance in the order of milliseconds. Many of the generated machine learning models can easily be run on any operating environment capable of running Java.
Teradata has also expanded the Teradata Listener’s IoT capabilities with connectors that simplify the acquisition and distribution of data from sensors for analysis. Acquiring and managing continuous data streams is a task that is usually complex and very laborious. With these new connectivity options, Listener will be able to provide new, faster and faster data flows of sensor data to Teradata Unified Data Architecture, both in the company and in the cloud.
The IoT Analytics unit is finally applying advanced machine learning techniques and analysis to system administration and DevOps activities. Machine learning techniques are applied to Teradata systems to solve problems related to performance and congestion due to workload in a matter of seconds.
The AoT technologies and services mentioned will be available from the second quarter of 2016.