Exploring the Interplay: Cloud Transformation and Enhanced Area Relations With Sol Rashidi

The intersection of cloud technology and artificial intelligence (AI) marks a critical point in contemporary technological advancement. This dynamic relationship between cloud transformation and AI innovation has become the cornerstone of numerous industries. It encompasses a myriad of challenges, opportunities, and evolving paradigms that shape how organizations leverage these technologies. To give us more insights into it, for this week’s CDO insights we have with us Sol Rashidi, former Chief Analytics Officer at the Estée Lauder, is acclaimed for her ability to unite technologists and non-technologists in leveraging data and technology for business growth. Recognized with prestigious awards like CAO of the Year and Top 100 Innovators in Data & Analytics, Sol excels in shaping strategic visions and execution strategies, guiding companies towards cohesive paths of success. Beyond her professional accomplishments, Sol is a dedicated parent, an active runner and krav maga enthusiast, and recently embraced golf. Her passion for exploration and empowering others to unlock possibilities defines her approach.

The interview delves into the interconnectedness of cloud transformation and AI, focusing on their symbiotic relationship and critical roles. It explores key considerations in AI application development using cloud technology and assesses the impact of lacking cloud resources on technical processes. Additionally, it discusses the balance between on-premises and cloud data strategies, talent prioritization, evolving concerns about data security and privacy, and anticipates the future dynamics of real-time data usage in cloud-AI relationships.

AIM: What drew your attention to the symbiotic relationship between cloud transformation and area relation as a podcast topic? Could you share the specific significance or relevance you find in these technologies that made you choose this subject?

Sol Rashidi: So, I've been in data analytics since the late '90s, when Excel was and still is the primary data tool used by many corporations and companies. But I've ridden the wave of business intelligence and data engineering and blockchain and IoT and CAMS initiatives and web 3.0 and Big Data and ML and Data Science and now AI, so I feel like every two to three years, there's a new buzzword that's come around, and everyone has a tendency of focusing on the user interface. These products are released out there. But there needs to be more attention to the backend workloads that fundamentally need investments or are needed even to make those applications work. And sometimes, we tend to gloss over how things are done and made. We go straight to the pretty product that everyone sees without a true appreciation of all the workloads, compute, GPU, CPU, Cloud Ops, identity access management, like the non-sexy stuff that no one talks about that seems very defensive driven, but fundamentally the power of the applications. And so it needed some attention in the space.