Data leaders powering data-driven innovation
In each episode we salute Champions of Data + AI, the change agents who are shaking up the status quo. These mavericks are rethinking how data and AI can enhance the human experience. We’ll dive into their challenges — and celebrate their successes — all while getting to know these leaders a little more personally.
Champion: Stuart Hughes, Chief Information and Digital Officer, Rolls-Royce
Data democratization starts with disruptive leadership. When data leaders simplify the data architecture and empower data teams with the right tools and creative freedom to do their best work, they unleash the true power of data.
Champion: Sol Rashidi, Chief Analytics Officer, Estée Lauder
Data leaders are updating their playbook with an offense that focuses on increasing business value with data and AI. Take Sol Rashidi, Chief Analytics Officer of Estée Lauder. She holds seven patents and was recently recognized as one of the 50 Most Powerful Women in Tech. In this episode, Sol dives into how she’s taking charge on product development to add business value, all while overcoming organizational challenges and becoming a change agent.
Champion: Jon Francis, Chief Analytics Officer, Starbucks
As data leaders design, develop and iterate on new data and AI products, it’s critical to maintain the human connection — especially in consumer-focused businesses. Jon Francis, Chief Analytics Officer of Starbucks, joins us to share insights from his experience leading data teams across some of the most iconic brands, including Starbucks, Nike, Amazon and Microsoft. Tune in to hear Jon share the challenges and responsibilities data leaders face in maintaining a healthy balance between using data ethically and driving new insights.
Champion: Kate Carruthers, Chief Data and Insights Officer, University of New South Wales, Sydney
From the onset of the COVID-19 pandemic, educational institutions had to quickly make the shift to teaching fully online. In this episode, Kate Carruthers, Chief Data and Insights Officer at the University of New South Wales Sydney, discusses how she’s helping transform the university into a data-driven organization. Kate and her team are delivering new insights to instructors and students, rapidly moving pilot applications to production, and creating innovative ways to combat new threats that challenge the sanctity of the code of ethics between students and the university.
Champion: JoAnn Stonier, Chief Data Officer, Mastercard
What happens when the data being used to improve customer experiences has unknown or inherent biases? JoAnn Stonier discusses the ethical use of data when implementing machine learning and AI use cases. She also shares her perspective on the steps that organizations can take to eliminate bias from showing up in the data.
Champion: Pallaw Sharma, Chief Data Science Officer, Supply Chain, Johnson & Johnson
When people think of data-driven organizations, you hear the same names again and again: Google, Netflix, Facebook and Uber. Often overlooked are large data-driven organizations like Johnson & Johnson that have thrived for decades by using data to make business decisions. Join us to hear Pallaw Sharma from J&J talk about the importance of having a well-curated data layer for all data types — structured, semi-structured and unstructured — so you can tackle all data and AI use cases.
Champion: Habsah Nordin, Head of Enterprise Data, Group Digital, PETRONAS
To have an effective enterprise data and AI strategy, you need to take a methodical approach to data management. In this episode, Habsah Nordin, the Head of Enterprise Data in Group Digital at PETRONAS, discusses her approach to building a data-driven organization that starts with a strong data management layer. We’ll also get her perspective on her experience as the first woman PETRONAS hired in this role — and what advice she has for aspiring data and AI leaders.
Global Principal Technologist at Databricks
From 2014 to 2020, Chris was responsible for leading Capital One’s enterprise data transformation initiative. Chris managed a 1,000 person data engineering team with a budget of $120 million-plus to develop cloud-native solutions and platforms for streaming data, data lake, on-demand compute, data warehouse, data management, data governance, business intelligence and machine learning. He was also responsible for migrating Capital One from on-prem versions of Teradata, SAS, Hadoop and Ab Initio to the new AWS-based Modern Cloud Data Architecture leveraging Databricks and Snowflake for various workloads.
Prior to Capital One, Chris founded, led and successfully exited a software company after serving as its president and CEO from 2002 through 2014. He served as an adjunct professor at George Mason University and the University of Virginia and is a frequent presenter at major technology conferences. Chris holds B.S. and M.S. degrees in Electrical Engineering with a concentration in Computer Science from Virginia Tech.