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 multicloud and open source, and continued high-performance from our global support organization were praised as strengths among other notable AI benefits like machine learning optimization and natural language querying.

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 — with an entire roadmap for their data science strategy.

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.

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 which has led to repositories of uncleansed and ungoverned data. This effect has created data that is very hard to use.

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.

In this blog post, we’ll share real-world stories of how decision optimization technology delivers prescriptive analytics capabilities and opens the door to operational efficiency. We will also introduce you to the IBM data science and AI platform solutions that can deliver operational efficiency that satisfies the business.

In the latest release of IBM Cloud Pak for Data, v2.5 has three key themes: Red Hat integration, new key built-in capabilities like Watson tools and runtimes, and a heavy focus on open source .(https://www.ibmbigdatahub.com/blog/announcing-cloud-pak-for-data-2-5). Open source is widely adopted in enterprises especially as products and vendors mature and expand their reach. We are expanding the support for open source technologies to our enterprise clients and ensuring the governance of all open source within an enterprise. Cloud Pak for Data v2.5 provides Analytics Engine powered by Apache Spark service integrated in the platform to give a holistic experience to the users to run serverless spark jobs for spark version 2.3 and 2.4 and take advantage of access control, logging, monitoring and many other integrated services.

Segmentation, targeting, positioning – how does an organization optimize these strategic approaches in the context of retention? Which factors should the segmentation take into consideration? This is where good information management and analytics come into play. Explore IBM’s solutions today: Modernization of your information architecture and Advanced Analytics.

A new generation is among us. They were born after 2010 into a world where technology is ubiquitous…We are witnessing the birth of a new intelligent species…While all under 10 years old, Siri, Watson and Alexa have already made an impact on the world and we can imagine the potential they all have…