In this last post of the series, I want to share a story that really demonstrates the power of this service on the mainframe. This summer two interns were assigned to a project under me. We were tasked with building an IT operational analytics dashboard using SMF data from the various mainframe systems that we have at Rocket. Our goal was to provide it to our system programmers for their day-to-day use and planning. Eli and Nick, our interns, had no previous mainframe experience and had never interacted with a mainframe. Eli had a computer science background and could pick up new technologies very easily. Nick, on the other hand, an avid builder, loved tinkering with hardware, had a robotics background and was looking forward to adding software experience to his belt.
Last month IBM commissioned Forrester Research to ask 200 IT leaders in the US, Europe, and Latin America about their current cloud computing deployments and theirs plans for the next two years. Most interestingly, though respondents overwhelmingly would prefer to deploy their systems in a private cloud, they hesitate to do so for lack of expertise both in implementing and managing such platforms. Respondents currently risk some security for the greater business advantages they perceive in deploying to hosted clouds.
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When we announced general availability of our flagship IBM dashDB data warehousing and analytics service in the cloud last year at the IBM Insight conference, we promised to the audience that we will not just make it the most easy to use analytic tool in the cloud, but also we will continuously add features and functionalities that add value to business users, data developer and data scientists. Since then we have introduced several new analytic models including k-means clustering and decision tree analysis. We have also been listening closely to hundreds of our dashDB customers and thousands of our community developers on what they like and what they like to have in the service. Data engineers want to see data set free so they can develop cool applications using the corporate data. More...
At this point in this series, you have installed the Rocket Mainframe Data Service on your mainframe and mapped some VSAM data on the mainframe to a virtual table. You are now ready to access the data from the Bluemix app and build a cloud or mobile app in Bluemix that will utilize the mainframe data for real time access to the all useful Systems of Record.
Learn how you can have a worry-free solution on-premises or in an IBM SoftLayer data center that is managed for you. Hear about detailed capabilities that IBM and Blue Box provide that are differentiators in the market. Also, learn how public cloud is the key to a hybrid scalable cloud solution. See how IBM's open cloud platform, Bluemix, integrates open technologies to enable client's developing cloud native applications using OpenStack infrastructure.
Earlier this year, IBM announced the availability of IBM Insights for Weather, a set of data services that tap into the breadth and depth of The Weather Company’s forecast and historical observational data. While IBM solution teams and Watson Analytics continue to deepen our weather-based solutions, IBM is proud to announce that we are now placing the capability to unlock value with weather data into the hands of the Bluemix developer community, IBM’s platform for cloud services and development. Developing weather-enabled applications is now easier than ever.
IBM BigInsights is an enterprise-ready Hadoop distribution designed to enable analytics on larger volumes of data more cost-effectively. We sat down with Rohan Vaidyanathan, the offering manager for BigInsights on Cloud, to talk about the major benefits of the cloud service and get the scoop on the enhancements coming down the pike this year. In part two, we’ll talk about the how companies are actively using BigInsights on their big data projects.
Although the large, open source community is the driving force behind the rapid adoption of Docker containers, many customers want the security and peace of mind of a commercially-supported solution. With an open source solution, the onus is on the end user to file and lobby for code fixes. On the other hand, a commercially-supported solution allows you to focus on your application and let Docker handle the bug fixes. With this in mind, Docker partnered with IBM to launch their first commercial offering – Docker Trusted Registry with commercially supported Docker Engines. While initially available in North America only, it is now available in Europe for businesses looking for a commercially supported Docker solution.