The relationship between AI and data professionals is evolving rapidly, creating both opportunities and challenges. As companies embrace AI-first strategies and experiment with AI agents, the skills needed to thrive in data roles are fundamentally changing. Is coding knowledge still essential when AI can generate code for you? How important is domain expertise when automated tools can handle technical tasks? With data engineering and analytics engineering gaining prominence, the focus is shifting toward ensuring data quality and building reliable pipelines. But where does the human fit in this increasingly automated landscape, and how can you position yourself to thrive amid these transformations? Megan Bowers is Senior Content Manager, Digital Customer Success at Alteryx, where she develops resources for the Maveryx Community. She writes technical blogs and hosts the Alter Everything podcast, spotlighting best practices from data professionals across the industry. Before joining Alteryx, Megan worked as a data analyst at Stanley Black & Decker, where she led ETL and dashboarding projects and trained teams on Alteryx and Power BI. Her transition into data began after earning a degree in Industrial Engineering and completing a data science bootcamp. Today, she focuses on creating accessible, high-impact content that helps data practitioners grow. Her favorite topics include switching career paths after college, building a professional brand on LinkedIn, writing technical blogs people actually want to read, and best practices in Alteryx, data visualization, and data storytelling. Presented by Alteryx, Alter Everything serves as a podcast dedicated to the culture of data science and analytics, showcasing insights from industry specialists. Covering a range of subjects from the use of machine learning to various analytics career trajectories, and all that lies between, Alter Everything stands as a celebration of the critical role of data literacy in a data-driven world. In the episode, Richie and Megan explore the impact of AI on job functions, the rise of AI agents in business, and the importance of domain knowledge and process analytics in data roles. They also discuss strategies for staying updated in the fast-paced world of AI and data science, and much more. Links Mentioned in the Show: Alter EverythingConnect with MeganSkill Track: Alteryx FundamentalsRelated Episode: Scaling Enterprise Analytics with Libby Duane Adams, Chief Advocacy Officer and Co-Founder of AlteryxRewatch RADAR AI  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

Whether big or small, one of the biggest challenges organizations face when they want to work with data effectively is often lack of access to it. This is where building a data platform comes in. But building a data platform is no easy feat. It's not just about centralizing data in the data warehouse, it’s also about making sure that data is actionable, trustable and usable. So, how do you make sure your data platform is up to par? Shuang Li is Group Product Manager at Box. With experience of building data, analytics, ML, and observability platform products for both external and internal customers, Shuang is always passionate about the insights, optimizations, and predictions that big data and AI/ML make possible. Throughout her career, she transitioned from academia to engineering, from engineering to product management, and then from an individual contributor to an emerging product executive. In the episode, Adel and Shuang explore her career journey, including transitioning from academia to engineering and helping to work on Google Fiber, how to build a data platform, ingestion pipelines, processing pipelines, challenges and milestones in building a data platform, data observability and quality, developer experience, data democratization, future trends and a lot more.  Links Mentioned in the Show: BoxConnect with Shuang on Linkedin[Course] Understanding Modern Data ArchitectureRelated Episode: Scaling Enterprise Analytics with Libby Duane Adams, Chief Advocacy Officer and Co-Founder of Alteryx 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

Everything in the world has a price, including improving and scaling your data and AI functions. That means that at some point someone will question the ROI of your projects, and often, these projects will be looked at under the lens of monetization. But how do you ensure that what you’re working on is not only providing value to the business but also creating financial gain? What conditions need to be met to prove your project's success and turn value into cash? Vin Vashishta is the author of ‘From Data to Profit’ (Wiley), the playbook for monetizing data and AI. He built V-Squared from client 1 to one of the oldest data and AI consulting firms. For the last eight years, he has been recognized as a data and AI thought leader. Vin is a LinkedIn Top Voice and Gartner Ambassador. His background spans over 25 years in strategy, leadership, software engineering, and applied machine learning. Dr. Tiffany Perkins-Munn is on a mission to bring research, analytics, and data science to life. She earned her Ph.D. in Social-Personality Psychology with an interdisciplinary focus on Advanced Quantitative Methods. Her insights are the subject of countless lectures on psychology, statistics, and their real-world applications. As the Head of Data and Analytics for the innovative CDAO organization at J.P. Morgan Chase, her knack involves unraveling complex business problems through operational enhancements, augmented financials, and intuitive recruiting. After over two decades in the industry, she consistently forges robust relationships across the corporate spectrum, becoming one of the Top 10 Finalists in the Merrill Lynch Global Markets Innovation Program. In the episode, Richie, Vin, and Tiffany explore the challenges of monetizing data and AI projects, including how technical, organizational, and strategic factors affect your input, the importance of aligning technical and business objectives to keep outputs focused on core business goals, how to assess your organization's data and AI maturity, examples of high data maturity businesses, data security and compliance, quick wins in data transformation and infrastructure, why long-term vision and strategy matter, and much more. Links Mentioned in the Show: Connect with Tiffany on LinkedinConnect with Vin on LinkedinVin’s Website[Course] Data Governance Concepts Related Episode: Scaling Enterprise Analytics with Libby Duane Adams, Chief Advocacy Officer and Co-Founder of Alteryx 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

Despite the critical role of analytics in guiding business decisions, organizations continue to face significant challenges in harnessing its full potential. As data sets expand and deadlines shrink, the urgency to scale analytics processes becomes paramount. What data leaders now need to focus on are essential strategies for analytics at scale, including fostering a culture of continuous learning, prioritizing data governance, and leveraging generative AI. Libby Duane Adams is the Chief Advocacy Officer and co-founder of Alteryx. She is responsible for strengthening upskilling and reskilling efforts for Alteryx customers to enable a culture of analytics, scaling the presence of the Alteryx SparkED education program and furthering diversity and inclusion in the workplace. As the former Chief Customer Officer, Libby has helped many Fortune 100 executives to identify and seize market opportunities, outsmart their competitors, and drive more revenue from their current businesses using analytics.  In the episode, Richie and Libby explore the differences between analytics and business intelligence, analytics as a team sport, the importance of speed in analytics, generative AI and its implications in analytics, the role of data quality and governance, Alteryx’s AI platform, data skills as a workplace necessity, using AI to automate documentation and insights, success stories and mistakes within analytics, and much more.  Links Mentioned in the Show: AlteryxAlteryx SparkED Program[Course] Introduction to AlteryxRelated Episode: From Data Literacy to AI Literacy with Cindi Howson, Chief Data Strategy Officer at ThoughtSpotSign up to RADAR: The Analytics 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