Susan dives into the evolving landscape of data quality, emphasizing the increasing importance of expertise in this area as AI technologies develop. She discusses the challenges faced in data cleaning, share real-world stories that highlight the impact of poor data quality, and provide practical tips for effective data management. The conversation also touches on the future of data quality in the context of AI, underscoring the need for human oversight and the ongoing relevance of traditional data management skills.

Erica discusses the importance of having a well-defined data strategy to enable organizational growth and scalability. The conversation covers challenges faced by both new and established organizations in implementing data strategies, the role of technology and data architecture, and the decision-making process between data centralization and data mesh. They emphasize the need for flexibility, understanding organizational needs, and the importance of aligning data strategies with business operations and talent mix.

Miguel dives into the intricate world of AI implementation, focusing on the pivotal role of data governance. Discover the challenges organizations face in managing data integrity, privacy, and compliance, and explore effective strategies to overcome these hurdles. Join us as we uncover insights from industry experts on balancing innovation with responsibility in the AI landscape.

In this conversation, Malcolm Hawker discusses his journey in podcasting, the insights from his upcoming book 'Data Hero Playbook', and the challenges faced by Chief Data Officers in articulating the value of data and a shift in mindset is necessary for data leaders to succeed. He emphasizes the importance of a customer-centric approach in data management and the role of AI in transforming data practices. The discussion also touches on the concept of data democratization and the future of data roles in organizations.

Chris Scholz, a seasoned finance and data consultant shares his expertise on bridging the communication gap between data teams and CFOs, emphasizing the importance of storytelling and understanding the business language. Discover how data teams can enhance their collaboration with finance departments to drive better decision-making and unlock transformative value. Tune in to learn practical strategies for fostering synergy and improving data-driven insights in your organization.

Bill Inmon discusses the evolution of data analytics, the importance of data quality, and the need for industry-specific taxonomies. He emphasizes the challenges of processing textual and analog data, and shares insights on sentiment analysis and the future of data processing.

Jolie discuss the challenges and strategies of building a value-centric data team. They emphasize the importance of forming close relationships with business partners, identifying value propositions, and effectively communicating the value of data initiatives. The conversation also touches on the balance between technical debt and delivering timely solutions, as well as the need for continuous improvement and adaptation in data practices.

Ken Tingle discusses the concept of data empathy, emphasizing the importance of understanding the needs and experiences of stakeholders in the business intelligence field. He shares his journey from sales to business intelligence, highlighting the challenges he faced in understanding data and the significance of building relationships with stakeholders. Ken provides practical tips for cultivating data empathy within teams, balancing organizational goals with stakeholder needs, and navigating office politics. He stresses the importance of communication and the potential impact of technology on empathy in the workplace.

Brent discusses the critical role of data storytelling in organizations, emphasizing that effective storytelling goes beyond mere data visualization. He outlines the importance of insights, the narrative arc, and the psychological aspects of visuals in engaging decision-makers. Brent also shares practical recommendations for crafting compelling data stories that resonate with audiences and drive actionable outcomes.

Charles Boyle, former Chief Data Officer/Chief Data Scientist, discusses the essential components of building and scaling a Data and AI Center of Excellence (COE). He emphasizes the importance of aligning team goals with corporate objectives, the critical role of technology, and the balance between insourcing and outsourcing resources. The discussion also covers strategic decisions regarding building versus buying technology solutions and the importance of measuring the value of data initiatives in relation to business goals.

Dawar shares insights on how data teams can drive business value by engaging with executives, understanding organizational goals, and measuring success through relevant metrics. They also explore the impact of AI on data teams, highlighting both its potential and the risks of overselling AI capabilities. Dawar also reflects on his career journey, offering advice on learning strategies and the importance of being a problem solver in the workplace.

Wyatt discusses the importance of building trust within organizations, particularly in the context of data analytics. They explore how analytics teams can drive value through cost savings, incremental improvements, and effective communication of their impact. The discussion emphasizes the need for a decentralized model, shared learning environments, and the significance of counter metrics in measuring success. Ultimately, the conversation highlights the challenges analytics teams face in demonstrating their value and the importance of strategic communication in fostering trust and collaboration within organizations.

Alex Ingram explores the importance of building emotional capital in the workplace, cultivating trust through relationships, and the process of selecting projects that add value to organizations. They discuss how genuine interest in colleagues can lead to better collaboration and project outcomes, as well as the emotional challenges that come with adopting new technologies and processes.

Preethi explains how ensure and enrich customer (business stakeholders) experience in the realm of business intelligence, and how these relate to the onboarding of AI initiatives. Preethi is currently holding a title of Chief of Staff, and on the advisory board of Lady of the Lake University and a member of the International Association of Women.

In this podcast Dr. Morales covers how to create a data culture within your organization. Dr. Morales has spent the last 20 years helping executives navigate analytics products and actionable insights to improve patient outcomes. Over and above her corporate influences she has leveraged 11 million in USDA and NIH funding for Children’s Nutrition, and Neurosurgery studies and has an Endowment scholarship named after.

Eric Gonzales has been providing data advisory services for fortune 500 companies on building a data pragmatic data foundation. It is with no surprise than that we ask Eric to discuss building a pragmatic data foundation to help provide some initial framework on how to do this at your respective organization.

Jennah James has been in data and analytics for over a decade with a plethora of experience across numerous industries including supply chain management, education, and media. In this podcast Jennah discusses how to determine what level of centralization or decentralization of data / business intelligence your organization should have and how to scale this at your respective organization.