To some, predictive machine learning is just another category of software, but when you look beyond the name? It’s a superpower. With predictive machine learning, everyone can perform wonders like a data scientist even with minimal “data science knowledge.”
Embedding predictive output within the software is what makes it so unique—the integrated analytics tool automates the data analysis process with machine learning. Predictive machine learning has filled in the gap between the business world’s high demand for predictive insights and the lack of available, trained data scientists.
Automated data processes have empowered business users to perform data analysis and access its benefits, triggering the birth of what we now call “citizen data scientists.”
Game-Changing Predictive Machine Learning Radio Series – Episode One
This emergence of the “citizen data scientist” was the topic of yesterday’s first episode in the new Game-Changing Predictive Machine Learning radio series, the Making of a Citizen Data Scientist: Challenges and Hacks.
The conversation was lively from beginning to end, with host Bonnie D. Graham bringing life and laughter to the conversation among her guests:
- Parimala Narasimha, Director for Advanced Analytics at Cox Communications
- Richard Mooney, lead product manager for the Predictive Analytics Product Portfolio, SAP
- Former Member , Global Vice President SAP Leonardo, AI & New Markets
- Erik Marcade, head of the Advanced Analytics development team within the SAP Leonardo and Analytics end-to-end unit of SAP
If you missed the action-packed and informative chat, you can listen to the replay. Here are some highlights:
- Richard explained that “We don’t need to be able to build an engine in order to drive a car” and neither do we need to have a data science degree to be able to reap the business benefits of machine learning insights.
- Marc described machine learning as not simply democratizing the analytic process, but rather “democratizing intelligence.”
- Parimala emphasized automating daily mundane tasks to focus on the bigger ones, suggesting that, “If you’re not automating any of what you’re doing, you’re not doing something right.”
- This statement aligns with Erik’s concluding prediction that in the coming years: “We will see a change of job descriptions as everything that can, should, be automated.”
And There’s Still More to Come…
Throughout the year, host Bonnie D. Graham addresses various buzzworthy topics in raw and thought-provoking dialogue with panels of prestigious experts—giving us answers to questions which we never even thought to ask. In the new Game-Changing Predictive Machine Learning radio series, Bonnie will bring that focus to predictive.
It is high time to rethink predictive machine learning’s disruptive and transformative potential—both inside and outside of the office. We hope you’ll join us for all our upcoming episodes.
Remember, if you can’t listen in real time, all episodes will be available for replay on the series webpage after they air. (You can go to the series page and bookmark the show to stay up-to-date.)
Join us live for the next episode on July 18th at 2pm EDT.
Learn more about predictive topics like this one by reading the other blogs in our Machine Learning Thursdays blog series.