Building a slide deck, pitch, or presentation? Here are the big takeaways:

  • IBM has unveiled Cloud Private for Data, a cloud platform that uses data science and machine learning to improve AI and help businesses make better decisions with data.
  • IBM is launching the Data Science Elite Team to consult customers on how they can best use big data to power their decision making.

On Friday, IBM launched a new cloud platform effort that will help customers better understand their data and use it to power their work in artificial intelligence (AI). Announced in a press release, IBM said the platform is “designed to provide a data infrastructure layer for AI behind the firewall.”

The Cloud Private for Data combines data science and machine learning to better grok the data that powers a firm’s business. And, it can do all this for a company, even if they don’t have a data science expert on their payroll, according to an IBM blog post.

In the press release, IBM bills the service as “an integrated data science, data engineering and app building platform.” Using Cloud Private for Data, firms can get deeper insights from their data and build intelligent apps with data collected from connected sensors, e-commerce platforms, and smartphones.

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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,” Rob Thomas, general manager for IBM Analytics, said in the release. “But for them to get there, they need to put in place an information architecture for collecting, managing and analyzing their data.”

Cloud Private for Data is an application layer, the release noted, and will be deployed on Kubernetes. According to the release, it only takes minutes to deploy. The platform relies on microservices to integrate data science into the application development environment. Vertical-specific versions will eventually be available for financial services, healthcare, and manufacturing.

IBM also announced a new free consultancy service called the Data Science Elite Team. The focus of the team is to help businesses better understand their data so they can use it to power AI initiatives. According to the release, the team will work on-sit with clients to help them integrate machine learning into their business processes.

The team starts with a client workshop where they identify a use case and examine the relevant data. From there, they look to identify three or four deliverables that can be executed in a few weeks. The client company is then provided with further strategies, methods, and technologies to power their machine learning efforts, the release said.

The Data Science Elite Team has 30 members currently, but is expected to grow to 200 sometime in the next few years, the release said.