IBM Research Launches New Big Data Lab
IBM announced the opening of its new Accelerated Delivery Lab, which is focused on solving problems involving big data.IBM Research has opened a new lab focused specifically on big data. On Oct. 10, IBM announced the Accelerated Discovery Lab, a new collaborative environment targeted at helping clients find unknown relationships from disparate data sets. Some of the industry applications being considered at the new lab are drug development, social analytics and predictive maintenance. IBM officials said the new workspace includes access to diverse data sources; unique research capabilities for analytics such as domain models; text analytics and natural language processing capabilities derived from IBM’s Watson supercomputer; a potent hardware and software infrastructure; and broad domain expertise including biology, medicine, finance, weather modeling, mathematics, computer science and information technology. This combination reduces time to insight, resulting in business impact—cost savings, revenue generation and scientific impact—ahead of the traditional pace of discovery, IBM said. IBM said each day society creates 2.5 quintillion bytes of data generated by a variety of sources—from climate information to posts on social media sites to purchase transaction records to health care medical images. Big data and analytics are a catalyst to help organizations become more competitive and drive growth, according to IBM. The company is helping its customers harness this big data to uncover valuable insights and transform their business. IBM also says it has established the world's deepest and broadest portfolio of big data technologies and solutions, spanning services, software, research and hardware.
The notion of Moore’s Law for big data has less to do with how fast data is growing, and more with how many connections one can make with that data and how fast those connections are growing, IBM said. While companies could utilize data scientists to analyze their own information, they may miss insights that can only be found by bringing their understanding together with other experts, data sources and tools to create different context and discover new value in their big data.