Generative AI has transformed the financial services sector, sparking interest at all organizational levels. As AI becomes more accessible, professionals are exploring its potential to enhance their work. How can AI tools improve personalization and fraud detection? What efficiencies can be gained in product development and internal processes? These are the questions driving the adoption of AI as companies strive to innovate responsibly while maximizing value. Andrew serves as the Chief Data Officer for Mastercard, leading the organization’s data strategy and innovation efforts while navigating current and future data risks. Andrews's prior roles at Mastercard include Senior Vice President, Data Management, in which he was responsible for the quality, collection, and use of data for Mastercard’s information services and advisory business, and Mastercard’s Deputy Chief Privacy Officer, in which he was responsible for privacy and data protection issues globally for Mastercard. Andrew also spent many years as a Privacy & Intellectual Property Council advising direct marketing services, interactive advertising, and industrial chemicals industries. Andrew holds Juris Doctor from Columbia University School of Law and has his bachelor’s degree, cum laude, in Chemical Engineering from the University of Delaware. Andrew is a retired member of the State Bar of New York. In the episode, Adel and Andrew explore GenAI's transformative impact on financial services, the democratization of AI tools, efficiency gains in product development, the importance of AI governance and data quality, the cultural shifts and regulatory landscapes shaping AI's future, and much more. Links Mentioned in the Show: MastercardConnect with AndrewSkill Track: Artificial Intelligence (AI) LeadershipRelated Episode: How Generative AI is Changing Leadership with Christie Smith, Founder of the Humanity Institute and Kelly Monahan, Managing Director, Research InstituteSign up to attend RADAR: Skills Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Countless companies invest in their data quality, but often, the effort from their investment is not fully realized in the output. It seems like, despite the critical importance of data quality, data governance might be suffering from a branding issue. Data governance is sometimes looked at as the data police, but this is far from the truth. So, how can we change perspectives and introduce fun into data governance? Tiankai Feng is a Principal Data Consultant and Data Strategy & Data Governance Lead at Thoughtworks, He also works part-time as the Head of Marketing at DAMA Germany. Tiankai has had many data hats in his career—marketing data analyst, data product owner, analytics capability lead, and data governance leader for the last few years. He has found a passion for the human side of data—how to collaborate, coordinate, and communicate around data. TIankai often uses his music and humor to make data more approachable and fun. In the episode, Adel and Tiankai explore the importance of data governance in data-driven organizations, the challenges of data governance, how to define success criteria and measure the ROI of governance initiatives, non-invasive and creative approaches to data governance, the implications of generative AI on data governance, regulatory considerations, organizational culture and much more.  Links Mentioned in the Show: Tiankai’s YouTube ChannelData Governance Fundamentals Cheat Sheet[Webinar] Unpacking the Fun in Data Governance: The Key to Scaling Data Quality[Course] Data Governance ConceptsRewatch sessions from RADAR: The Analytics Edition New to DataCamp? Learn on the go using the DataCamp mobile app Empower your business with world-class data and AI skills with DataCamp for business

There is a concept in software engineering which is called ‘shifting left’, this focuses on testing software a lot earlier in the development lifecycle than you would normally expect it to. This helps teams building the software create better rituals and processes, while also ensuring quality and usability are key aspects to evaluate as the software is being built. We know this works in software development, but what happens when these practices are used when building AI tools? Saurabh Gupta is a seasoned technology executive and is currently Chief Strategy & Revenue Officer The Modern Data Company. With over 25 years of experience in tech, data and strategy, he has led many strategy and modernization initiatives across industries and disciplines. Through his career, he has worked with various Internation Organizations and NGOs, Public sector and Private sector organizations. Before joining TMDC, he was the Head of Data Strategy & Governance at ThoughtWorks & CDO/Director for Washington DC Gov., where he developed the digital/data modernization strategy for education data. Prior to DCGov he played leadership and strategic roles at organizations including IMF and World Bank where he was responsible for their Data strategy and led the OpenData initiatives. He has also closely worked with African Development Bank, OECD, EuroStat, ECB, UN and FAO as a part of inter-organization working groups on data and development goals. As a part of the taskforce for international data cooperation under the G20 Data Gaps initiative, he chaired the technical working group on data standards and exchange. He also played an advisor role to the African Development Bank on their data democratization efforts under the Africa Information Highway. In the episode, Adel & Saurabh explore the importance of data quality and how ‘shifting left’ can improve data quality practices, the role of data governance, the emergence of data product managers, operationalizing ‘shift left’ strategies through collaboration and data governance, the challenges faced when implementing data governance, future trends in data quality and governance, and much more.  Links Mentioned in the Show: The Modern Data CompanyMonte Carlo: The Annual State of Data Quality Survey[Course] Data Governance Concepts[Webinar] Crafting a Lean and Effective Data Governance Strategy Related Episode: Building Trust in Data with Data Governance New to DataCamp? Learn on the go using the DataCamp mobile app Empower your business with world-class data and AI skills with DataCamp for business

In this episode of DataFramed, Adel speaks with Barr Moses, CEO, and co-founder of Monte Carlo on the importance of data quality and how data observability creates trust in data throughout the organization. 

Throughout the episode, Barr talks about her background, the state of data-driven organizations and what it means to be data-driven, the data maturity of organizations, the importance of data quality, what data observability is, and why we’ll hear about it more often in the future. She also covers the state of data infrastructure, data meshes, and more. 

Relevant links from the interview:

Connect with Barr on LinkedInLearn more about data meshesCheck out the Monte Carlo blogDataCamp's Guide to Organizational Data Maturity