Making Data Simple host Al Martin looks back on his top 5 favorite clips from episodes published in 2018. These conversations range from explaining the importance of data visualization, to discussing the differences between A.I. and deep learning. Thanks to all of our listeners for an incredible
Jason Tatge, CEO, president and cofounder of Farmobile, joins the show to discuss data in the agriculture industry. The conversation touches on Jason's experience launching a startup, tips for finding success, and the value of big data from a farmer's perspective. This episode gives insight to data
On this episode of the Making Data Simple podcast, Al Martin sits down with Jean Bozman, vice president at Hurwitz & Associates, and Dan Kirsch, managing director at Hurwitz & Associates. Together, they discuss data optimization, compliance, governance, and security in industries including
IBM is well-known for its powerful legacy of design throughout the 1980s. But the company’s focus on design dimmed until Phil Gilbert stepped up to the plate in 2010 and instilled design thinking throughout the company, empowering a legion of designers. The focus on hiring talent, investing in
If you’ve heard the debate among IT professionals about data lakes versus data warehouses, you might be wondering which is better for your organization. You might even be wondering how these two approaches are different at all.
This episode of Making Data Simple features Brian O’Neill, product designer for Designing for Analytics. Brian and host Al Martin step back from the deep, technical questions of data science, architecture and governance to look at how principles of design can clarify and accelerate development for
At TOTAL, we understand that running an oil well profitably and efficiently is mechanically and technically complex. That’s why we are always looking for new ways to innovate and become more efficient.
The business that gets there first won’t necessarily win digital and AI game. It will be the one that ingrains digital and AI in its business as much as possible. Starting from applying intelligent data science where it matters most and progressively using it in every aspect of the business.