AT&T has unveiled a new data analytics capability in the form of a pilot collaboration between AT&T and IBM. The new AT&T IoT analytics service will run on the IBM Watson Data platform over the cloud, allowing clients real-time access to industrial IoT data to assist with immediate operational decision-making.
The new service will combine various IoT data-gathering solutions offered by AT&T including M2X, Flow Designer, and Control Center with the IBM Watson data platform, which uses machine learning to drive analytics and promote effective real-time decision making. The IBM Watson IoT portfolio will allow customers to build, launch and manage apps and devices to support IoT data while providing analytics to help improve performance.
The pilot program that launches today is the result of the strategic partnership between AT&T and IBM, announced in July 2016. The two companies created the partnership to take advantage of complementary capabilities in data gathering and machine learning driven analytics, to maximize IoT functionality for enterprise clients and accelerate IoT adoption.
Earlier this month, AT&T and IBM joined companies such as Nokia and Symantec to create an IoT cybersecurity alliance, to address IoT-related security challenges.
Chris Penrose, President of IoT Solutions for AT&T, said that the integration of IBM Watson with AT&T’s IoT products will be a huge asset for enterprise clients.
“We have more than 30 million connected devices on our network today and that number continues to grow – primarily driven by enterprise adoption,” he said. “Businesses are eager for actionable data insights from their connected devices that help improve their processes and take the guesswork out of decision-making.”
For example, a company can create a machine learning library and data filter to help predict device malfunction or failure. A client can take the data collected through the AT&T IoT network and run it through Watson analytics to create preventative maintenance alerts, keeping costs low and improving customer service.
A 2016 survey showed that the number of connected devices worldwide is expected to reach 50 billion by 2020. As IoT adoption grows across industries, data extraction techniques will become more important for clients looking to apply data to real-time decision making.
Using IBM’s machine-learning driven platform to analyze IoT data is intended to increase the effectiveness of decision-making by combining and extracting data from IoT devices in meaningful and useful ways. Clients can maximize device performance for customer satisfaction, while at the same time increasing efficiency and keeping their own costs down through smart data analytics and real-time responses.