Recent offerings in the container space sparked a lot of buzz about Docker, Kubernetes, and ISTIO. Where does IBM stand in all of this? Let’s take a closer look… IBM Bluemix Container Service builds on open source technology to provide production-ready security, life-long node management, and accelerated innovation for multi-container apps. You can move enterprise-grade […]
Built on Watson Data Platform, IBM Data Catalog is IBM’s next-generation, cloud-based enterprise data catalog. It promises to provide a central solution where users can catalog, govern and discover information assets, and it is designed to slash the time spent searching for and hesitating over sharing data, so that you can focus on extracting business value from your data assets.
Data governance is rarely seen as a glamorous topic, and even the mere mention of the ‘G’ word often inspires groans and yawns from non-specialists. But are they missing a trick? It’s possible that the failure to appreciate data governance comes from a lack of understanding about the value it can deliver, and just how important it is to future success. Today, we’re going to attempt to address that gap in understanding. First, let’s define our terms: by data governance, we’re referring to the overall management of the availability, usability, integrity, and security of the data employed in an enterprise. A sound data governance program includes a defined set of procedures, a plan to execute those procedures, and people who are responsible for putting that plan into action. This might sound like a lot of work without much payoff—but the truth is that data governance plays a key role in ensuring that data is used to its full potential.
IBM’s aim with Watson Data Platform is to make data accessible for anyone who uses it. An integral part of Watson Data Platform will be a new intelligent asset catalog, IBM Data Catalog, a solution underpinned by a central repository of metadata describing all the information managed by the platform. Unlike many other catalog solutions on the market, the intelligent asset catalog will also offer full end-to-end capabilities around data lifecycle and governance.
With cases of both type I and type II diabetes rising, Medtronic recognized the need to create a new generation of glucose monitoring solutions that would give people the tools to manage their diabetes more easily, in combination with routine support from healthcare professionals. Find out how they are working with IBM Watson to help.
Today, we're proud to announce the launch and immediate availability of the brand new Db2 Warehouse on Cloud Web console and REST APIs! We want to make your interaction with our world-class cloud data warehouse offering as seamless as possible, so we set out to completely redesign these two integral parts of our user experience.
We're rebranding dashDB for Analytics to Db2 Warehouse on Cloud.
For decades now, SQL has been the colossus of data management query languages. Generations of database administrators, developers and analysts have built highly successful careers around tables and foreign key relationships, to the point where thinking about data in a relational schema has become second nature. In fact, many believe that relational databases are still the only safe and effective way to model complex data relationships.
In recent years, technologies that enable organizations to capture, process, ingest and analyze large volumes of data at high velocity have become increasingly important.