Data Mesh vs. Data Lakehouse: Choosing the Right Architecture
The data architecture landscape has never been more fragmented. Here's a pragmatic framework for choosing the right approach based on your organization's maturity.
Lisa Wang is the Chief Data Officer at Plaxonic Technologies, where she shapes enterprise data strategy, governance frameworks, and analytics architecture for global clients. With over 12 years of experience in data engineering and analytics, Lisa has built scalable data platforms processing petabytes of data for some of the world's largest organizations.
Her career spans roles across data engineering, business intelligence, and data science leadership. Before Plaxonic, Lisa was the Head of Data Platforms at a leading fintech company, where she architected a real-time data mesh serving 200+ data products across the organization.
Lisa holds a Master's degree in Data Science from UC Berkeley and is a certified Databricks Data Engineer and Snowflake Data Architect. She has spoken at Strata Data Conference, dbt Coalesce, and Data Council on topics including data mesh implementation, real-time analytics, and data governance at scale.
At Plaxonic, Lisa leads the Data & Analytics practice, helping enterprises navigate the evolving data landscape—from traditional data warehousing to modern data mesh and lakehouse architectures. She is passionate about democratizing data access while maintaining governance and quality standards.