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
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
Global data privacy compliance regulations like the General Data Protection Regulation (GDPR),California Consumer Privacy Act (CCPA) and Brazil’s LGPD have created scrutiny around personal, customer and employee data. This data is growing at a rapid pace, and so are the mandates requiring
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 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 --
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.
The number of business segments requiring data to drive contextual insights is increasing. Leaders are seeking new ways to manage the pressures of delivering high-quality data faster across their businesses. To date, many of these projects have focused solely on ingesting data into a data lake
Learn how marine solution provider James Fisher and Sons plc and the IBM Data Science and AI Elite team surge towards a renewable tomorrow with the electrifying power of data visualization built on IBM Watson Studio.