Emerson Gatchalian, the CDAO of the Blackbelt Team within Microsoft, shares his expertise on modern data platforms. He discusses the evolution of data governance strategies and the balance between centralization and decentralization. Gatchalian also dives into the cost-effectiveness of adopting existing solutions like Microsoft Fabric versus custom builds. Furthermore, he highlights how integrating AI with data can enhance customer service and drive innovation, particularly through utilizing unstructured data in generative AI applications.
Implementing a modern data platform necessitates a shift to adaptable architectures that enhance collaboration while maintaining strict governance standards.
To effectively leverage AI, organizations must focus on fostering collaboration between IT and business units, ensuring unified access to diverse data sources.
Deep dives
Understanding the Modern Data Platform
A modern data platform enables organizations to optimize their data operations and prepare for advancements such as AI. This involves a shift from traditional, monolithic systems to flexible, federated solutions that encourage collaboration while maintaining core governance practices. Implementing such a platform requires understanding its architecture, including how different units within the business can operate autonomously while adhering to overarching rules of governance and data management. The ultimate goal is to empower business units to engage with their data effectively, transitioning from outdated tools like Excel to more integrated, scalable analytics solutions.
Lessons from Microsoft's Data Journey
Microsoft's experience in transforming its data practices offers valuable insights for organizations looking to modernize. Key lessons include avoiding the pitfalls of being overly monolithic while fostering a culture that emphasizes flexibility and discipline across departments. The approach should balance centralized governance with decentralized execution, allowing for individual units to leverage data effectively without creating silos. By managing duplication and ensuring traceability of data through proper governance tools, organizations can better understand their data landscape and encourage efficient data usage.
Starting Points for Digital Transformation
Organizations seeking to initiate modernization should consider multiple layers simultaneously, including culture, technology, and governance. Starting with easily demonstrable value within three to six months can build momentum for broader initiatives and foster a sense of achievement. Governance serves as the foundation by helping organizations understand their data assets, classifying them, and building appropriate policies around their security and access. Following governance, unifying data without duplication becomes essential for ensuring seamless analytics and avoiding the creation of new silos.
Integrating AI with Modern Data Practices
The integration of AI with modern data practices involves leveraging various data types, spanning structured and unstructured data sources to derive actionable insights. A robust data strategy includes not only effective data management but also fostering collaboration between IT and business units to maximize AI's benefits. Utilizing platforms like Microsoft Fabric facilitates access to unified data, enhancing the potential for innovative AI applications that draw insights from diverse data streams. Ultimately, organizations should prioritize foundational elements such as governance and automation to unlock the full potential of AI in their digital transformation efforts.
Are you struggling to better understand what it means to implement a modern data platform, and why doing so is relevant to your business?
If yes, check out this week’s episode of the CDO Matters Podcast, where Emerson Gatchalian, the CDAO of the Blackbelt Team within Microsoft, shares his insights on how his largest clients and Microsoft are implementing more adaptable, scalable, and AI-ready data infrastructures.