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Data Management // AI/Machine Learning
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The Right Fit: Choosing an AI Strategy

Dun & Bradstreet is transforming its own internal AI and analytics operations, even as it helps customers with their analytics and machine learning transformations.

How does your organization compare to its peers in terms of artificial intelligence implementations today? Do you feel as if you are behind? Rest assured, even if you don't have a program in place today, you are in good company.

If you are looking for a clear picture of where enterprise organizations are in terms of artificial intelligence implementation today, you're going to get a very mixed picture. Some organizations may be very advanced. Others may be struggling to get control over their data management and governance efforts. And, there's a range of companies that fall in between those two extremes.

Nipa Basu

Nipa Basu

Nipa Basu, Chief Analytics Officer at Dun & Bradstreet, has an insider view to what companies are doing with their analytics operations. She leads the AI transformation at Dun & Bradstreet, and she also works with many of Dun & Bradstreet's customers, large and small, in different vertical industries. She shared some of her perspective at the recent H2O World 2018 conference in New York, and she also spoke with InformationWeek in an interview.

AI reality check: One size does not fit all

One of the important lessons for organizations that are getting started with AI is that one size does not fit all. Basu told InformationWeek that companies need to focus their AI efforts on the elements of the business that are core to what they do.

For instance, Dun & Bradstreet's core mission includes performing advanced analytics better than anyone else does. Basu said that her team of mathematicians, econometricians, statisticians, and data scientists are focused on the analytics and not on building a software or platform for AI. Her team doesn't have data engineers.

But the system that her team uses can't just be a platform that lets you click a button and get the answer, because then her customers would be able to do the same thing. Providing advanced analytics insights is core to Dun & Bradstreet's value proposition.

Similarly, Basu said, another presenter at the H2O conference was a large accounting firm. That firm does not provide analytics services to other organizations as its core mission. But it does apply advanced analytics technologies to the things that are its core mission. Determining financial risk versus value was a core part of that firm's mission, for instance, so that's where that firm should focus its machine learning and artificial intelligence efforts.

(Image: xresch/Pixabay)

(Image: xresch/Pixabay)

Right-size your platform

Each organization must choose the platform that fits their own needs, depending on where they are in their journeys, Basu said. You wouldn't place a graduate student in a kindergarten class, or vice versa.

"It depends on who you are. If you are a company and you have an advanced team of data scientists, you go for the platform that will be helpful to get your young and aspiring data scientists up to speed fast," she said. "If you are a company where you don't have data scientists, then go for something less expensive and easier to use. Get something that fits where you are."

Dun & Bradstreet's journey

Where does Dun & Bradstreet fit on that continuum? Basu said there are many positive changes to how her organization works. In terms of processes, she said that the company has adopted Lean and Agile approaches and are seeing the benefits from that. Dun & Bradstreet has also broadened its approach to technology partnerships.

"We started with the big names and industrial strength systems," Basu told me. "We haven't backed away from that. But as an analytics leader, I feel a great need to work with companies that have established themselves in Silicon Valley in recent years."

These aren't trivial changes for a 175-year-old company.

An essential ingredient: The human element

Machine learning, AI and analytics advances will change the way we work and our workforce, but that doesn't mean it will eliminate the need for human workers. Basu told me that for these technologies to work well, they need humans.

"I think there may be too much reliance on the machine," she said. "I believe that the true good solution comes from a combination of human and artificial intelligence."

Basu said that human intelligence contributes domain knowledge, and "that's incredibly important."

You now have a sense of what D&B is doing with data science. See what other organizations and leaders are up to:

Overstock Accelerates with Big Data Platform

Data Science on a Budget: Audubon's Advanced Analytics

Self-taught Kaggle Champ: Engineering to Data Science to AI

GSK Updates Analytics Platform for Faster Drug Development

Jessica Davis is a Senior Editor at InformationWeek. She covers enterprise IT leadership, careers, artificial intelligence, data and analytics, and enterprise software. She has spent a career covering the intersection of business and technology. Follow her on twitter: ... View Full Bio

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