Semiconductor IP News and Trends Blog
Big Data Means Big Business for Semi IP
Vast amounts of machine-to-machine and human data promise plenty of work for information analysis and semiconductor IP designers.
Machine data will form a big part of the emerging Product-in-Life intelligence metrics, according to Laura Wilber, Solution Analyst, Exalead at Dassault Systemes. Her prediction is supported by a recent Analysis Mason Limited study, which found that machine-to-machine (M2M) device connections will grow to 2.1 billion by 2021. That’s up from an estimated 100.4 million device connections in 2011.
Product-in-Life intelligence refers to the gathering of machine and human data about a product once it’s in the market. Machine-to-machine data can come from anywhere – inside factories (e.g., sorters in postal services), inside automobiles, traffic-light cameras, power-company smart meters, mobile devices, and more.
Human data comes from social media, emails, online product reviews, etc. This type of data does require natural language processing to filter out meaningful information.
During her presentation at Dassault Systemes’s 3DExperience conference, Wilber talked about the challenges that big data places on traditional data-analysis tools and techniques. “The data generated by today’s systems are not suited for transaction-based relational databases,” she explained. “Such traditional systems cannot handle the volume, variety, and velocity of the (M2M and human) data.”
These challenges will also present employment opportunities for information engineers and semiconductor IP designers.
Why should IP designers care about this flood of M2M and human data? Doesn’t this flood lie in the realm of big data analysis? All of that is true, but the growth of M2M and even human data (especially in mobile devices) translates directly into the growth of sensors, microelectromechanical systems (MEMS), and analog technologies. Additionally, M2M data often relies on low-power wireless systems (see figure) and even energy harvesters – all of which require semiconductor IP designs, tools, and integration.