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IBM has expanded its Cloud Data Services range with over 25 cloud data services and 150 publicly available datasets now available on the IBM Cloud to aid developers in building, deploying and managing web and mobile applications. The services also allow data scientists to ascertain unseen trends using data and analytics in the cloud.
The hybrid cloud services can be implemented across multiple cloud providers. They hinge upon open source technologies, open ecosystems that include company and third-party data, and open architectures that allow data to move among different services. IBM is facilitating self-service competencies that range from data preparation, migration, and integration, to tools for advanced data exploration and modeling.
Derek Schoettle, IBM general manager for analytics platform and cloud data services, said: “Data is the common thread within the enterprise, regardless of where its source might be. In the past, data handlers have relied on disparate systems for data needs, but our goal is to move data into the future by providing a one-stop shop to access, build, develop and explore data.
“IBM’s integrated Cloud Data Services give developers greater scalability and flexibility to build, deploy and manage web and mobile cloud applications, and enable data scientists to apply information across businesses efficiently,” he added.
IBM has introduced a number of new cloud data services such as IBM Compose Enterprise, which is a managed platform formulated to aid developers in building modern web-scale apps faster by enabling them to implement business-ready open source databases in minutes on their own dedicated cloud servers. IBM Graph is a fully managed graph database service built on Apache TinkerPop that provides developers a complete stack to extend business-ready apps with real-time recommendations, fraud detection, IoT and network analysis uses.
IBM Predictive Analytics is a service that facilitates development of self-build machine learning models from a comprehensive library into applications to help deliver predictions for specific product use cases, without the help of a data scientist. IBM Analytics Exchange is an open data exchange that possesses a catalogue of more than 150 publicly available datasets that can be used for analysis or integrated into applications.
