IBM Launches Watson-Enabled Data Platform

The power of machine learning has arrived for the masses, and it comes in the form of a cloud-based platform called IBM Watson Data Platform.

Announced today in Las Vegas at the IBM World of Watson conference, the platform promises to let businesses get more valuable insights, as well as interpret and collaborate with data.

“Watson Data Platform applies cognitive assistance for creating machine learning models, making it far faster to get from data to insight,” said Bob Picciano, SVP of Information & Analytics.

“It also provides one place to access machine learning services and languages, so that anyone, from an app developer to the Chief Data Officer, can collaborate seamlessly to make sense of data, ask better questions, and more effectively operationalize insight.”

#IBM Picciano:announcing #Watson Data Platform for AI-powered decision making. "We're the only company doing this." #IBMWoW #makedatasimple

— IBM Data, AI & Automation (@IBMData) October 25, 2016

Why a Data Platform, and Why Now

In 2016, machine learning was moving out of research labs and into ordinary businesses, but most companies weren’t set up for it. Building a useful model takes clean data, people who know how to work with it, and tools that let those people share their work. In many organizations, all three lived in different departments.

That’s the problem IBM was pitching this platform against. Rather than a single new product, it was an attempt to put data access, analysis tools and collaboration in one place in the cloud. Analysts at Constellation Research described its key ideas as access control, governance and a shared, collaborative workspace.

Harness Collaboration

The IBM Watson Data Platform uses machine learning to intelligently and automatically build models from structured and unstructured data.

Citing a survey by Harvard Business Review, IBM says 80 percent of companies struggle with allowing employees to collaborate using common data, which in turn impacts a company’s ability to drive business results.

Businesses are siloed. People spend too much time collecting and then cleansing data, or they lack a consistent view of data across departments.

SVP @IBMAnalytics @bobpicciano at #ibmwow announces the Watson Data Platform to unleash the power of data.@IBM #DigitalTransformation #IoT pic.twitter.com/WZJgbfchtW

— Roberto Villa (@RobertoVjlla) October 25, 2016

That changes, IBM says, with the announcement of IBM Watson Data Platform, as different areas of the business will have access to a dashboard tailored to their specific needs and speciality.

“Access to data insights are no longer heavily dependent on IT,” Picciano said.

Insight will be the new currency, measuring the success of a company's #IT systems, says @bobpicciano at #ibmwow pic.twitter.com/kuvefmjSQO

— Tech Ed Canada (@TechEdCA) October 25, 2016

Built on Open Languages

SQL, Python, R, Java, and Scala are currently integrated into the system, as well as more than 20 ecosystem partners including RStudio, and APIs from Keen IO.

Watson Data Platform available on an open source foundation built on Spark. #ibmwow pic.twitter.com/UiycgMa6eT

— IBM Consulting (@ibmconsulting) October 25, 2016

That list matters more than it might seem. Data scientists tend to be loyal to the languages they already know, and Python and R in particular are where much of the open-source machine learning work happens. A platform that forced everyone into a proprietary tool would have struggled to win them over, so supporting the languages people already used was a practical way to get adoption.

Follow TechPortfolio on Twitter for up-to-date news and pictures from IBM World of Watson.

What Happened Next

IBM reshuffled its data business within months. In January 2017, a reorganization merged the analytics unit Picciano had run with IBM’s cloud division under Arvind Krishna, while Picciano moved to lead the newly named Cognitive Systems hardware business.

The tools kept evolving too. IBM’s Data Science Experience, a notebook environment for data scientists launched in 2016, was renamed IBM Watson Studio in 2018, and in 2023 it was rebranded again as watsonx.ai Studio.

That last change was part of a bigger reset. On May 9, 2023, at its Think conference, IBM unveiled watsonx, an AI and data platform with three parts: watsonx.ai for building and deploying models, including generative AI, watsonx.data for storing governed data, and watsonx.governance for managing how AI is used. The pitch was strikingly similar to 2016’s: one place where data, models and the people who work on them come together.

What It Means for Businesses

Product names have changed several times since this launch, but the problem IBM described in 2016 hasn’t gone away. Machine learning projects still stall more often on scattered, messy data and disconnected teams than on the algorithms themselves.

For any company starting out with AI, the lesson is to fix the plumbing first. Agree on where your data lives, who can use it and how it’s kept clean, and make sure the people building models can see each other’s work. Whatever platform you pick, that groundwork is what turns data into results.