Video: 10 Minute IT Jams – Who is DataRobot?

Automation is changing the world. At the centre of this transformation is DataRobot, a company focused on bringing cutting-edge machine learning solutions to businesses across the globe. During a recent interview, Tim Young, Asia-Pacific General Manager for DataRobot, shed light on how automation, particularly in the form of machine learning, is redefining the way organisations operate- especially as they face unprecedented risks and disruptions.

"DataRobot sells an automated machine learning platform that automates the development of machine learning models," Young explained. "Machine learning, which is part of artificial intelligence, has become very fashionable these days because it's all about automating business processes. Machine learning models use historic data in order to make predictions about the future."

He painted a picture of everyday applications: from identifying customers likely to leave, to spotting fraud, to detecting potential defects in products. The power of predictive analysis, he said, is now within reach for organisations of every size. "You may want to identify which of your customers are going to churn, which are going to respond to offers, whether you've got people committing fraud in your organisation, or even spotting new market opportunities," he said.

Young's views are supported by industry analysts. "Gartner, in their latest top 10 strategic technology trends, called out hyper-automation as their number one trend," he emphasised. The impact of the COVID-19 pandemic, Young argued, has only accelerated the need for automation. "Organisations have realised that they're very, very exposed. They have a huge amount of risks associated with such catastrophic events. When companies have to start sending all of their employees home, that is creating massive exposure and massive risk."

For Young, automation is a failsafe in uncertain times. "I think Gartner is calling out automation as a key trend because it addresses this risk. A business can operate in a more of a lights-out mode," he added, reflecting on the shift towards relying less on human presence in the event of disruptions.

Not just for experts, DataRobot's platform caters to a wide audience: "It's intended for expert data scientists, citizen data scientists, software developers, or anyone who wants to use machine learning to predict the future," Young said.

Looking back at his own experience in IT, Young pointed out how technological change has always been about automating manual processes. "I remember when I first was working in the IT industry back in 1987, I was working as a COBOL programmer. Now, no one would use COBOL today for software engineering purposes- that's because largely automated techniques have allowed companies to build and deploy applications very quickly. Automated machine learning is just a natural evolution of the trend of manually constructing machine learning algorithms."

DataRobot, he claimed, has been at the forefront of this evolution, launching the world's first automated machine learning platform in 2015. But, he conceded, "This is a trend that other vendors have embraced. Google have AutoML, and even Microsoft last year announced their own automated machine learning capability. This is a natural evolution and absolutely should be on every IT manager's agenda."

Recent months have been busy for the company, with new products and improvements rolling out at pace. "The three products that make up DataRobot are Paxata, which is a company we acquired recently- they provide a self-service data preparation software that gets the data ready for machine learning," Young said, noting the perennial problem businesses face of having disparate data across many systems. Paxata helps to pull this data together and make it "machine-learning ready".

Another key development is the launch of "ML Ops", which brings together DataRobot's existing deployment and monitoring tools with new capabilities following the acquisition of a company called ParallelM. "ML Ops is all about deploying and monitoring models, making sure that they remain fresh in light of business changes," Young explained. Significantly, ML Ops now supports third-party models developed outside of the DataRobot environment, "and that's necessary to support an all-encompassing machine learning strategy."

At its core, DataRobot's ML Dev product remains central to its offering, supporting regression, time-series, and classification models, and making use of open-source algorithms. Recent updates include the integration of "visual AI" and deep learning, as well as improved automated feature engineering. "Our goal is to get from data to prediction as quickly and as easily as we possibly can," Young said.

The company is also investing in the future of data science education. "Yesterday we announced something called the Applied Data Science Academy. This is a training program that's all about getting business analysts, data analysts, and citizen data scientists up to data science standards," he said. The free course includes 60 hours of online training and 40 hours of practical tests. For those affected by current economic disruptions, "that could be an interesting course- a business analyst who wants to beef up their skills and add elements of data science to their bow. I think that would be something that I would certainly recommend."

Closer to home, DataRobot has a solid presence in the Australia and New Zealand markets, with an office in Sydney. "We're supporting Australia and New Zealand from that office and we also have partners on the ground in New Zealand and so we're working through partners," Young said.

Asked about how prospective partners or enterprises can engage with the company, Young offered a touch of humour: "Well, they can make their cheques payable to DataRobot and they can send them through to me," he joked, before adding: "Seriously, just send me an email or get contact information for our Sydney office."

Reflecting on the company's progress and prospects, Young concluded, "There's lots going on, but those are just some of the things that I pulled out from the last few months."