Leveraging Biomedical Big Data: A Hybrid Solution
Innovate Digital Services To Accelerate Business Growth and Opportunities
Data Analytics: New Edge for Success
Turning Big Data into Big Money
Finding Talent is a Challenge
Max Mortensen, CIO, Norwegian American Hospital
Leveraging the Power of the Enterprise to Streamline and Secure DoD's IT
Terry Halvorsen, CIO, US Department of Defense
Our Calling and Time
Vincent A. Marin, CIO, Sidley Austin LLP
ERP: A New Age of Innovation
William R. Dyer, CIO, Cincom Systems, Inc
Big Data and Predictive Maintenance
Predictive maintenance is the new enormous thing. While big data gives the capacity to gather a huge measure of information, no one anticipated that it would drastically change the way we deliver things. Be that as it may, utilizing vast amounts of information to anticipate when, where, and even how an instrument may fail, can have a noteworthy effect on a business' primary concern.
For instance, impromptu machine failures for producers in Great Britain are assessed at excess of £180bn year-on-year. For smaller organizations, this can vary between a few thousand pounds in the quick-moving shopper products industry up to millions in the automotive industry.
( Expert's ViewPoint: Turning Bigdata into Big Money )
Big data has constantly held the guarantee to convey efficiencies in the way we fabricate and create merchandise and convey new experiences through the entire process. However, it can go significantly more remote than that and can be utilized to absolutely re-compose plans of action. Big Data is constantly redefining a change in the outlook of how we look at entire enterprises.
One of the primary advantages of big data is estimating when a machine or apparatus needs servicing before it stops functioning as planned. This is predictive maintenance—where an administrator can design upkeep through scheduled downtime before a genuine issue manifests. This brings down costs while at the same time increases the life of the machine.
You may like: Integration and Agility Are Key to Leveraging Big Data in Life Sciences
By Kim Shah, Director-Global Marketing & Business Development for the Informatics Business, Thermo Fisher Scientific