With the amount of choices surrounding big data analytics, data lakes and AI, it can sometimes be difficult to tell fact from fiction. With more than 40% of organizations expecting AI to be a “game changer,” it’s important to have a complete picture of the capabilities and opportunities available.
Owens-Illinois (O-I), the world’s largest manufacturer of glass containers, recently undertook a global migration from Oracle to Db2. Learn more about the migration and its success from O-I executives.
A company only survives for 115 years by reinventing itself, questioning assumptions, and constantly looking for an edge. Owens-Illinois (O-I), the world’s largest manufacturer of glass containers, used worldwide by many leading food and beverage brands, recently began just such a reinvention.
Today's manufacturing organizations operate in a dynamic environment characterized by increased complexity and uncertainty. The financial performance of manufacturers hinges on their ability to rapidly adapt to constantly-changing conditions, from demand fluctuations to delivery challenges while
Line-of-business (LoB) stakeholders want to know that their analytics investment will help them make better, faster, and smarter decisions, with measurable business results. But for many, measuring success from applying Machine Learning and Decision Optimization is not obvious. Learn the top 3
The manufacturing industry finds itself embroiled in major changes these days, and analytics, cloud-based technologies, the Internet of Things and volumes of data are fueling its metamorphosis. See how manufacturing companies are shifting resources toward value-add processes such as
Road-ready 3D-printed vehicles are no longer the stuff of imagination but of rapidly approaching reality. But how can Internet of Things connectivity and smart technology help keep drivers’ eyes on the road and their hands on the wheel? Discover how safe, smart and sustainable devices are bringing
Designing for the Internet of Things means creating new ways of achieving business goals, offering customers a compelling value proposition with connectivity at its forefront. Find out what considerations can help you reshape your business model to scale with the Internet of Things.
In practical terms, what does the fourth Industrial Revolution really mean to industrial manufacturers, and what is actually different now? Here are some examples of how the fourth Industrial Revolution is transforming the manufacturing and industrial landscape.
Automotive and manufacturing organizations deal with a massive volume of data, including global data from customers and data generated through internal business operations, research and development (R&D) and supply chain activities. These data sets represent an opportunity for an organization
Big data (data from many sources, of varying formats, both structured and unstructured) means different things in different industries. But as different as their needs and usage of big data may be, there is one commonality among all industries: the opportunity to plumb big data for better, more
I grew up in the Detroit area in the 1960s and 1970s, so I'm quite familiar with the wrenching dislocations caused by a manufacturing-based sector that was too stodgy and overbuilt to adapt in a pinch. Coming of age in an ancient industrial zone, you bear witness to how rapidly a smokestack economy