Goto

Collaborating Authors

"The Purple People" - The conundrum of finding business expertise among Data Scientists.

@machinelearnbot

Over the last several months, as I looked at addressing the business needs across various industries as someone leading a team of Data Scientists, the question of domain expertise invariably cropped up. Attending one meeting with a Pharmaceutical company, I was posed with the question of, "Have you done work in the areas of Rare Signal detection?" In a similar vein, while preparing for a meeting with an Auto finance major, the question was in the area of using Auto telemetry data and deploying it to work on fraud detection in auto-insurance claims. Multiply the business problems with the numerous industries and the enormity of the challenge becomes apparent. More so since it may not be possible to be a domain expert in every possible industry.


The Best Approach to Decision Making Combines Data and Managers' Expertise

#artificialintelligence

Data-driven management has risen sharply from a decade ago, when Thomas Davenport wrote Competing on Analytics. Data is now the critical tool for managing many corporate functions, including marketing, pricing, supply chain, operations, and more. This movement is being further fueled by the promise of AI and machine learning, and by the ease of collecting and storing data about every facet of our daily lives. But has the pendulum swung too far? Are managers relying excessively on data to guide their decisions, abdicating their own knowledge and experience?


Gen 3.0 analytics: How the government can use the data it owns

#artificialintelligence

This column was originally published on Jeff Neal's blog, ChiefHRO.com, The government is sitting on a treasure trove of HR data that it does not typically use. For example, agencies have data about performance, and data about where they recruit and what kinds of questions they ask in job announcements. I do not know of a single agency that is comparing the questions they ask to the performance they get from the selectees. There are so many possibilities to use the data to produce actionable information that would help agencies do better hiring, get better performance, and use their resources more wisely.


SAS: AI everywhere demands partners domain expertise - ChannelBuzz.ca

#artificialintelligence

As it moves to embed artificial intelligence and machine learning throughout its product line, SAS executives say the company will look to its growing base of partners to bring domain expertise to make that artificial intelligence actually intelligent. At its Global Forum event in Denver last week, the company announced that AI would become a common feature across its offerings. And CMO Randy Guard told ChannelBuzz.ca at the event that the biggest untapped opportunity for the company's partners is in connecting that AI capability with their own knowledge. "If you're going to solve a problem an AI product, you've got to bring your domain expertise, and marry the two of those together," Guard said. "As we start embedding AI and intelligence in everything we do, our partner community needs to recognize how that can be applied to the business scenarios they're solving for their customers."


A Critical Shift in Thinking About AI and Big Data

#artificialintelligence

Success with these technologies hinges on how companies marry AI and big data with business domain expertise--a C-suite imperative that cannot be ignored. Machine learning and big data have steadily increased their penetration of corporations over the past few years. And if we are to believe the articles we read, the era of artificial intelligence (AI) is now firmly upon us. It's fair to say we are just starting to dip a toe into this new world, but with new advances being made regularly, we need to prepare for a very different future. Putting aside the dystopian views that sensationalize AI, bright prospects are ahead for corporations that embrace this transition to new ways of thinking.