The IBM Data Science and AI Elite team showed that PostNord can predict non-deliveries of traceable items depending on address, weather condition, sizes and time of delivery. By leveraging AI, it’s possible to reduce non-deliveries by 50 percent annually, beneficial for both customers and PostNord
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.
Imagine a day in the life of Sarah, a hypothetical Chief Data Officer at a major bank in South Africa. There are many expectations on her shoulders. She struggles to deliver business-ready data to fuel her organization and support the decision makers within the bank. It is her job to put in place a
DataOps is the orchestration of people, process, and technology to accelerate the quick delivery of high-quality data to data citizens. When done right, DataOps creates business value because users know what data they have, can trust the quality and its meaning, and use it without violating
High-quality data is the core requirement for any successful, business-critical analytics project. It is the key to unlock and generate business value and deliver insights in a timely fashion. However, stakeholders across the board are responsible for data delivery, quickly evolving requirements,
The expectation to achieve faster results continues to rise. Businesses everywhere are looking for ways to improve their operational efficiency and effectiveness to enable the best decision-making. The need to optimize typically comes to a head with the reality that there are many silos within any
Most businesses collect data but are unable to use it to generate business value or deliver insights in a timely fashion. Data volume and data types continue to grow, as do the different types of data citizens—ranging from business users to data scientists. As a result, data management and delivery
All industries—from healthcare to retail to banking—are digitally transforming themselves every day to become more agile and stay competitive. However, all industries depend on data to be successful, and this impacts the way enterprises plan and execute their operations. Although enterprises have
At IBM Cloud Pak for Data, we’ve got a growing ecosystem of technology partners. As an open, Kubernetes-based, data and AI platform, we integrate with an array of tech solutions that enhance what we do to help companies make their data AI-ready. From stepping up data security to empowering
With its electro-light tulip garden, disco ball-adorned trees and no stone-left-unturned music lineup, "Denmark’s Most Beautiful Festival" aims to surpass guests’ expectations on safety, comfort and entertainment, from its uncannily clean bathrooms down to its whimsical camp-in-a-beer-can glamping
More companies are choosing to implement multicloud platforms that include software as a service (SaaS) due to the many opportunities, advantages, and benefits they provide. However, a recent ISG report, “Multi-Cloud Adoption Accelerates,” notes that a lack of proper planning could introduce
With the publication of Gartner’s 2019 Magic Quadrant (MQ) for Operational Database Management Systems, we were happy to see recognition of some of our key efforts from the past year. The integration of the Db2 common SQL engine and other rich features, edition simplification, commitment to
James Fisher & Sons had hearty ambitions to build predictive maintenance capabilities for its customers' subsea cables -- but lacked the right data to do so. In a creative pivot, the IBM Data Science and AI Elite team delivered more than what the heritage engineering company bartered for --
The future of banking is transforming. From changing customer behavior and expectations, rapid innovation in digital technology, burgeoning regulatory requirements, and the macroeconomic environment, the very definition of financial services is changing. For banks to stay relevant, they need to
Haruto Sakamoto, the Chief Information Officer at a Japanese multinational imaging company, had a few challenges to contend with. His business units had a presence in 180 countries worldwide with geographically-dispersed data warehouses and business intelligence applications in various locations.