The Data Fabric Show
Welcome to The Data Fabric Show where we explore what it means to create a modern data experience for everyone in an organization, from data analysts to non-technical business users. Each episode features interviews with data leaders, practitioners, and experts who share their insights and strategies for designing and delivering exceptional data experiences that drive business value.
Episodes

37 minutes ago
37 minutes ago
Joyce L. Myers, CDO of MTSI, considers herself more of a "builder" digital officer who's architecting additions to an already successful foundation.
In this episode of The Data Fabric Show, Joyce tells Kaycee her approach to building upon the strong foundation of an employee-owned defense contractor with a 31-year history. She explains how MTSI recognized the need for better data organization as they continued to grow, comparing their situation to an entrepreneur with too many files in cabinets who can't find what they need.
Joyce discusses the unique challenges of implementing data governance and AI solutions within the constraints of the public sector and defense industry, where security and protection of proprietary, sensitive, and classified information are paramount concerns. This security context creates additional complexity when adopting GenAI tools, requiring careful consideration before implementing solutions that might expose sensitive data.
Topics discussed:
The architectural challenges of integrating data governance as the first CDO in a 31-year-old employee-owned defense contractor, requiring a "builder" mentality to preserve institutional knowledge while implementing modern practices.
How defense-specific security constraints create unique implementation pathways for GenAI, requiring careful validation processes and air-gapped environments that balance innovation against protection of classified information.
The implementation of a trust-driven data quality framework that transforms "garbage in, garbage out" to "goodness in, goodness out."
Strategies for enabling secure self-service analytics within highly regulated environments, emphasizing documented iterative processes that capture decision context for future governance and compliance requirements.
The evolution from tightly-controlled ETL processes toward a more agile data fabric approach that creates a sandbox environment for experimentation before formalizing pipelines.
The comprehensive metadata context needed to create effective data products in defense applications — capturing not just data lineage but decision authority, classification levels, and intended analytical purpose.
Applying NASA's mission-focused organizational alignment to defense data teams, where every contributor understands how their component supports operational objectives regardless of technical specialty.
The development of an iterative data discovery workflow for security-conscious environments that preserves context while enabling business users to safely explore and refine analytical questions.

Tuesday Jan 07, 2025
Tuesday Jan 07, 2025
In this episode of The Data Fabric Show, Kaycee speaks with Bruce Desmarais, PhD, Professor & Director of the Center for Social Data Analytics, Penn State University. Together, they dive into the role of advanced data science tools in analyzing social media data to address issues like misinformation and online bullying.
Bruce shares insights on the collaboration between academia and tech companies. The conversation also explores the transformative potential of generative AI in social research, including the creation of synthetic social systems for experimentation.
Topics discussed:
The significance of social data analytics in understanding human behavior and communication through digital traces left on social media.
Challenges researchers face in accessing and integrating diverse data sources, especially with changing data formats and proprietary data restrictions from social media companies.
The importance of collaboration between academia and industry in addressing real-world problems, with examples of successful partnerships that enhance data analytics efforts.
The role of generative AI in streamlining data analysis processes, including its potential to automate data tagging and quality checks in research.
Ethical considerations in social research, particularly when experimenting with interventions on social media platforms and the implications for freedom of speech.
The impact of generative AI on survey design and data collection, allowing researchers to generate realistic synthetic responses for more efficient analysis.
The need for data validation and quality checking in research, emphasizing the importance of unit testing to ensure accurate results from AI-generated outputs.
The future of social data analytics and the potential for creating synthetic social systems to explore complex interactions without ethical concerns or real-world consequences.
The ongoing challenges of data governance and security in enterprise analytics, highlighting why many organizations are hesitant to fully adopt generative AI technologies.

Monday Dec 02, 2024
Monday Dec 02, 2024
In this episode of The Data Fabric Show, Kaycee speaks with Robin Sutara, Field Chief Data Strategy Officer at Databricks, who shares her unique journey from repairing Apache helicopters in the U.S. Army to leading data strategies in the tech industry.
Robin dives into the importance of fostering a data-driven culture within organizations and the critical role of change management in digital transformation. Additionally, Robin discusses how generative AI can enhance data strategies, emphasizing the need for robust data foundations to ensure trust and accuracy in AI outputs.
Topics discussed:
The significance of fostering a data-driven culture within organizations is crucial for successful digital transformation and maximizing the value of data initiatives.
How change management is essential for ensuring that new technologies are embraced by business users, bridging the gap between tech and business needs.
How generative AI is revolutionizing data strategies by automating processes, enhancing data quality, and enabling organizations to make more informed decisions.
The importance of data governance and transparency in building trust around AI outputs, ensuring that users can rely on the data provided.
Why organizations must focus on creating simple, consistent user interfaces that allow business users to engage with data without needing extensive technical knowledge.
The need for collaboration between technical teams and business users to align data initiatives with organizational goals and drive meaningful outcomes.
The necessity of investing in data foundations to support generative AI and ensure the accuracy and reliability of insights generated.
The evolving landscape of AI and data technologies requires organizations to remain adaptable and open to integrating new solutions into their existing ecosystems.

Thursday Oct 17, 2024
Thursday Oct 17, 2024
In this episode of The Data Fabric Show, Kaycee speaks with Matt Clark, Data Leader of National Grid Electrical Transmission, who shares his expertise on the evolving landscape of data leadership. He discusses the various roles of CDOs, including the caretaker, arsonist, phoenix, and scapegoat, highlighting the unique challenges and opportunities each role presents.
Matthew emphasizes the importance of empowering business users to take ownership of data and analytics, fostering a culture of collaboration and innovation. He also explores how emerging technologies like data fabric and GenAI can enhance data accessibility and quality, paving the way for more effective decision-making in organizations.
Topics discussed:
The evolving role of chief data officers, including caretaker, phoenix, arsonist, and scapegoat, and how these roles impact organizational effectiveness and culture.
The importance of understanding organizational culture when stepping into a data leadership role and how it influences the success of data initiatives.
Strategies for empowering business users to take ownership of data, fostering a culture of accountability and collaboration within organizations.
The challenges data leaders face when trying to drive transformation and innovation in organizations resistant to change and traditional practices.
The role of emerging technologies, such as data fabric and GenAI, in enhancing data accessibility, quality, and overall decision-making processes.
The significance of aligning data strategies with business objectives to ensure that data initiatives deliver tangible value to the organization.
The necessity of building strong relationships with stakeholders to gain buy in for data initiatives and ensure successful implementation.
The impact of rapid technological advancements on data workflows and the need for data leaders to adapt to these changes effectively.

Wednesday Sep 25, 2024
Wednesday Sep 25, 2024
In this episode of The Data Fabric Show, Kaycee speaks with Dr. Ram Singh, Chief Data Officer at Night Market, who shares his expertise on the intersection of data analytics and marketing. He emphasizes the significance of composable analytics in driving tangible business outcomes and enhancing customer experiences.
Dr. Singh discusses the importance of rapid prototyping, which fosters innovation and collaboration within organizations, allowing teams to uncover unexpected use cases. Additionally, he explores the evolving role of AI in marketing, highlighting its potential to optimize processes and improve customer engagement. Dr. Singh offers valuable insights on aligning analytics with business goals and leveraging data for success in today’s competitive landscape.
Topics discussed:
How composable analytics enables businesses to integrate data sets effectively, leading to improved decision-making and enhanced customer experiences.
The importance of demonstrating measurable business results from analytics initiatives is emphasized, ensuring that data-driven strategies align with organizational goals.
How rapid prototyping encourages innovation and collaboration, allowing teams to quickly test ideas and adapt to changing business conditions.
The evolving role of artificial intelligence in marketing is explored, focusing on its ability to optimize processes and drive customer engagement.
The necessity of leveraging data to inform strategic decisions, ultimately leading to better business performance and competitive advantage.
The importance of cross-functional collaboration in data projects, fostering a culture of shared insights and collective problem-solving.
Strategies for extracting value from data in smaller increments, allowing businesses to see results without lengthy implementation timelines.
The need for analytics initiatives to be closely aligned with overarching business objectives to ensure relevance and impact.
The significance of maintaining a customer-centric focus in analytics, ensuring that insights directly enhance customer experiences and satisfaction.
The common challenges organizations face in integrating various data sources, offering insights on overcoming these obstacles for better analytics outcomes.

Tuesday Sep 17, 2024
Tuesday Sep 17, 2024
In the second episode of The Data Fabric Show, Kaycee Lai, Founder of Promethium, and Ramon Chen, CPO at Acceldata, discuss the dynamic world of data observability as a critical function for ensuring data quality, cost efficiency, and operational effectiveness. They explore the emerging relevance of active metadata, which enables organizations to leverage AI for building smarter data products and managing data more effectively, as well as the challenges and benefits of integrating data observability with active metadata and how it creates a more comprehensive view of data lineage and quality, enhancing trust in data for AI applications.
Ramon also shares his insights on modernization strategies, such as migrating data from legacy systems like Hadoop to the cloud, while using data observability to avoid moving redundant or irrelevant data, and critical need for visibility across the data pipeline to prevent inefficiencies and ensure a clear understanding of the data landscape. Throughout the episode, they emphasize the importance of balancing technology and business goals, understanding market needs, and fostering collaboration between business and IT to achieve a modern, efficient, and transparent data experience.
Listen in for practical insights on creating a data-driven strategy, leveraging AI, and building a modern data observability framework that aligns with your organization's objectives.
Topics discussed:
The importance of data observability in identifying and resolving data quality issues before they escalate into costly problems.
The "shift left" approach, which advocates addressing data quality at the point of entry to enhance overall efficiency.
How active metadata can provide essential context, improving trust and understanding of data across organizations.
The transformative role of generative AI in data management, enabling better insights and decision-making capabilities.
The need for collaboration between data teams and business users to ensure data-driven decisions are informed and effective.
The necessity of having end-to-end visibility in data pipelines to understand dependencies and potential impacts on business operations.
The evolving role of chief data officers and the challenges they face in maintaining data governance and quality.
The effectiveness and efficiency of various tools used for data quality management and their associated costs.

Wednesday Sep 04, 2024
Wednesday Sep 04, 2024
In this episode of The Data Fabric Show, our host, Kaycee Lai, Founder of Promethium, speaks with Peggy Tsai, Chief Data Officer at BigID. Peggy shares her expertise on the evolving role of data governance in today’s organizations. She discusses the importance of leveraging AI technologies to enhance data initiatives and the critical need for effective communication with stakeholders.
Peggy also emphasizes how CDOs can navigate challenges by focusing on building trust and collaboration within their teams. Additionally, she highlights the significance of storytelling in articulating the value of data-driven strategies. Peggy offers valuable insights into the strategies that can help CDOs succeed in an increasingly complex data landscape!
Topics discussed:
How the responsibilities of Chief Data Officers are changing in response to technological advancements and organizational needs.
Common challenges CDOs face in implementing effective data governance frameworks within their organizations.
The importance of integrating AI into data strategies to enhance efficiency and drive better decision-making processes.
The need for CDOs to establish trust and collaboration with stakeholders is crucial for successful data initiatives and project buy-in.
The importance of clear communication in articulating data solutions and addressing the needs of various stakeholders.
How achieving quick wins can help CDOs build credibility and demonstrate the value of data initiatives to leadership.
The significance of storytelling in conveying the impact of data projects and making complex data concepts accessible to all.
How a deep understanding of business objectives is essential for CDOs to align data strategies with organizational goals and drive value.
The importance of investing in employee education and upskilling to adapt to evolving data landscapes.
Strategies for CDOs to manage relationships with vendors and ensure they align with the organization's data strategy and goals.