Initiatives at IBM Corp. to provide clean, workable data science for all types of business have driven internal pursuits for innovation at a company that’s been around more than 100 years. Vikram Murali (pictured), program director of the Watson data platform at IBM, and his team utilize new strategies, established procedures, and strong partnerships to provide the best data science experience.

“Our goal is for us to enable data scientists in their path to gain insights into data using data science techniques, machine learning … open source and be able to collaborate with fellow data scientists, with data engineers and business analysts,” Murali said.

The data science experience started with Murali and his team talking to customers, data scientists, engineers and enterprises about their individual problems, and then figuring out how to address them. “It’s all about freedom, giving freedom to data scientists to pick the tool of their choice … program and code in the language of their choice. That was the mission of Data Science Experience when we started this,” he said.

Murali spoke with Dave Vellante (@dvellante) and John Walls (@JohnWalls21), co-hosts of theCUBE, SiliconANGLE’s mobile livestreaming studio, during the IBM Data Science for All event in New York City. They discussed the most challenging roadblocks in data science and IBM’s multi-faceted approach to improving integration processes for companies at every level. (* Disclosure below.)

Re-architecting for new challenges

Murali and his team pair IBM’s established tools with new methodologies to customize offerings for the many varied clients they service today. “Previously integrating them into our product would have been a nightmare. … But now with the microservice architecture, it is very easy,” Murali said.

The team also works closely with Hortonworks Inc. so Hadoop customers can more efficiently leverage service. “We set up joint engineering teams; we have multiple touchpoints every day. … Today data science experience can authenticate using secured Knox. … And that was a direct example of our partnership with Hortonworks,” he said regarding the Apache Knox Gateway, a REST API Gateway for interacting with Apache Hadoop clusters. Murali expects deeper integrations to come between IBM and Hortonworks to further simplify the customer experience.

The greatest difficulty for data scientists continues to be the sheer volume of unstructured data that must be cleaned in order to provide any business value — and their tendency to work in silos makes IBM’s task of addressing data quality issues at the enterprise level even more challenging. Data Science Experience solves these issues, according to Murali.

“Now we provide … the tools of your choice, open source or proprietary. … You can do all the work that you need … as well as collaborate with other data scientists in the enterprise,” he said.

With six releases this year with the Data Science Experience and continuous cloud delivery, Murali is enthusiastic about what he and his team have accomplished, and they are showing no signs of slowing down. “[We’re] adding features that our customers are asking for and not making them wait for three months, six months, one year. That is [possible] because of the team. … We are very agile,” he concluded.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of the IBM Data Science for All event. (* Disclosure: TheCUBE is a paid media partner for the IBM Data Science for All event. Neither IBM, the event sponsor nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE