Teradata announced two new breakthrough software capabilities that empower business users to uncover and operationalize the insights hidden within Internet of Things (IoT) data. These were 1. Teradata® Listener™ and 2. Teradata Aster® Analytics on Hadoop make it possible to intelligently listen in real-time and then use analytics to see the distinctive patterns in massive streams of IoT data.
And while Teradata does agree that we are in the age of over 50B connected devices, generating a massive and constant stream of data, the focus has not been on ingesting and maximizing value from the data with machine learning algorithms. Even the most technology-savvy organizations recognize that extracting value from data generated by the IoT is a difficult, skills-intensive process. Even more difficult is integrating the IoT data with business operations and human behavioral data.
Why the Internet of Analytics? Teradata’s latest innovative IoT software capabilities eliminate complexity and latency, while providing organizations with entirely new capabilities to leverage data. Teradata Listener is intelligent, self-service software with real-time “listening
” capabilities to follow multiple streams of sensor and IoT data wherever it exists globally, and then propagate the data into multiple platforms in an analytical ecosystem. Data propagated to the recently-released Teradata Integrated Big Data Platform 1800 provides access to large volumes of data with its native support of JSON (Java Script Object Notation) data. Data propagated to Hadoop® can be analyzed at scale with Teradata Aster Analytics on Hadoop.
What Does This Mean To YOU? Let’s take for example, a Teradata customer and major manufacturer who sells and services magnetic resonance imaging (MRI), radiography, and ultrasound imaging equipment to global hospitals and clinics. With thousands of patient scans daily, these medical devices have become indispensable in global healthcare. Text logs describing patient behavior and sensor data are streamed 24/7 from the equipment into the manufacturer’s Hadoop data lake. Teradata runs text analytics on the data to uncover insights that help global field service personnel improve machine up-time and extend maintenance windows. Simultaneously, data from the equipment manufacturing process flows into a Teradata Appliance where advanced analytics offer insights for improving quality and manufacturing efficiency and help ensure that problems are not passed to the next product generation.
What Products / Services Were Announced?
- Teradata Listener – Teradata Listener is intelligent, self-service software for ingesting and
distributing fast-moving data streams–either individual or multiple streams–at one time. It allows customers to push data to Hadoop, Teradata Aster Analytics, Teradata Database, and other platforms. It enables data scientists, business analysts, and developers to quickly and easily analyze new data streams for faster answers to business questions. Without needing to rely on IT for help, users can analyze data from numerous sources including sensors, telematics, mobile events, click streams, social media feeds, and IT server logs.
2. Teradata Aster Analytics on Hadoop – Unique in the industry, the enhanced Aster Analytics on Hadoop is an integrated analytics solution from Teradata now featuring a set of more than 100 business-ready, distinctly different analytics techniques and seven vertical industry applications to run directly on Hadoop®. This allows organizations to seamlessly address business problems with an integrated analytics solution.
The flexibility and simplicity of these capabilities enables everyday business analysts to perform as data scientists by tackling the organization’s most challenging problems. Teradata Aster Analytics on Hadoop allows users to combine machine learning, text, path, pattern, graph, and statistics within a single workflow. Teradata offers flexible Aster Analytics deployments that includ
e the Teradata Big Analytics Appliance, Hadoop , the software only version, or in the Teradata Cloud. And not all clouds are created equally!
4. Teradata Integrated Big Data Platform 1800
Released on Monday, October 19, the Teradata Integrated Big Data Platform 1800 is the ideal platform to support the new IoT capabilities. It enables customers to perform complex ana
lytics at scale and is available at a cost-effective price of approximately $1,000 per terabyte of compressed data. The Teradata Database, running on the Teradata Integrated Big Data Platform, provides access to data in many formats, including XML, name-value pair, BSON (Binary JSON) and JSON from web applications, sensors, and Internet of Things-connected machines.
5. Think Big is First to Offer Comprehensive Managed Services for Hadoop Data Lakes
Many organizations have found that it is relatively easy to download Hadoop software for free, and then load their data. What is far more difficult is to gain a competitive advantage from analyzing big data. The problem is compounded as a result of the current shortage of talented individuals with Hadoop skills. Organizations need individuals who understand the complexities of building and operating distributed systems, and have experience with managing systems at scale. Think Big consulting teams can manage data lakes and build applications with their highly trained and field-tested engineers, developers, and data scientists
“Think Big Managed Services for Hadoop help customers drive business results by building an analytical ecosystem that ensures data quality, reliability, and day-to-day completion of operational tasks,” said Ron Bodkin, president, Think Big. “Hadoop is a maturing technology with a range of challenges. Think Big offers world-class service to help customers address the common Hadoop platform and application challenges.”
For more info check out these links:
- Up-coming Webinar, November 16: Real Time Data Streams: What’s in it for Me?
- Teradata Listener Data Sheet
- Teradata Aster Analytics on Hadoop Data Sheet
- Teradata Integrated Big Data Platform 1800 Data Sheet
With all the devices and data, we have to work at making sure we are not collecting data for the sake of collecting data. Data has to be cleansed, managed and mined for insights that drive real business results.
@DrNatalie, VP and Principal Analyst, Constellation Research
