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IBM’s Private Cloud for Data simplifies enterprise data science

Announced in a press release on Friday, IBM said the new platform will be compatible with “all” cloud networks. It’s based on the Kubernetes container architecture, an open-source modularisation system originally created by Google. Applications developed using Cloud Private for Data can be deployed in minutes to cloud environments.
The platform is engineered to assist businesses in building new apps and utilising data. IBM is specifically positioning the cloud to uncover “previously unobtainable insights” that could help companies streamline their operations. Cloud Private for Data can ingest information from a wide range of sources, including data science utilities, industrial sensors, ecommerce transactions and mobile devices.
According to IBM, the platform will enable enterprises to “bring the AI destination closer” by making it simpler to harness the value of data. The service will provide a way for firms to convert data into actionable insights, without requiring complex siloed applications. IBM claimed that Cloud Private for Data can analyse up to one million data events each second while supporting cloud applications and microservice containers.
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“Whether they are aware of it or not, every company is on a journey to AI as the ultimate driver of business transformation,” said Rob Thomas, General Manager, IBM Analytics. “But for them to get there, they need to put in place an information architecture for collecting, managing and analyzing their data. With today’s announcements, we are planning to bring the AI destination closer and give access to powerful machine learning and data science technologies that can turn data into game-changing insight.”
Although the solution is compatible with all cloud ecosystems, IBM will also offer a range of industry-specific solutions. These will be optimised for workloads such as financial services, healthcare and manufacturing, providing insights that are most relevant to these industries. Enterprises will be able to configure AI services and data analysis pipelines without using external services, creating an integrated environment for app development and data science.
To encourage adoption of Cloud Private for Data and its other data services, IBM is also establishing a dedicated customer support team. The company’s new Data Science Elite Team currently includes over 30 individuals but is expected to grow to more than 200 people over the next few years. The team assists customers in using IBM’s platforms and configuring their workloads, further lowering the learning curve for AI and data science.

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