Modern Data Management
Automate Smarter. Scale Faster.
Streamlining data workflows, automating processes, and scaling infrastructure—without the headaches. Get practical strategies for effective data analytics and engineering.
What I Do
Automate Workflows
Eliminate repetitive tasks and streamline processes using scalable automation.
Build Scalable Infrastructure
Design robust, modern data stacks that grow with your business needs.
Deliver Actionable Insights
Turn complex data into clear, decision-ready reporting and dashboards.
Featured Blog Posts
Why Parquet Beats CSV for Modern Data Work
CSV got us started, but it struggles at scale: bloated files, messy schemas, and painfully slow queries. Parquet flips the model—storing data in compact, labeled columns that query faster, compress better, and form the foundation of modern lakehouses. In this post, I use a Lego analogy to show why Parquet isn’t just a file format upgrade, it’s the workshop behind today’s analytics.
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Modern Data Architecture Explained Through the Kitchen
Modern data architecture can feel like alphabet soup: databases, warehouses, lakes, lakehouses, catalogs. With Microsoft Fabric making Delta Lake the default, it’s never been more important to understand how these systems fit together. In this post, I use a kitchen metaphor to break down the strengths and weaknesses of each—lunchboxes, buffets, pantries, and chefs—before looking at DuckLake, a new approach that puts metadata where it belongs: in a database. The goal isn’t hype, it’s clarity—so you can design an architecture that feeds your business real insight.
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The Next-Gen BI Tool Isn’t a Tool — It’s a Kit
Traditional BI tools prioritize speed and ease but often sacrifice flexibility and customization. Today, the rise of AI, modular libraries, and instant cloud platforms like Replit empower data engineers to build highly customizable, interactive, and user-focused data experiences—without needing full-stack development expertise. This shift transforms BI from rigid, one-size-fits-all dashboards into composable, code-assisted data product kits that deliver tailored insights and enable narrative-driven storytelling. Discover how the future of BI is no longer a monolithic platform but a flexible toolkit that bridges data engineering and user experience seamlessly.
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Do You Really Need Data Modeling? A Practical Look
Data modeling has been the backbone of structured analytics for decades, ensuring consistency, performance, and reliability. But with modern storage affordability, faster processing, and flexible BI tools, the necessity of rigid data models is evolving. This post explores when traditional modeling adds value—and when startups and agile teams can thrive by embracing more flexible, denormalized, or hybrid approaches. Learn how to balance structure and speed to deliver impactful insights without over-engineering your data pipeline.
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About Me
I'm a data engineer passionate about building clean, scalable systems and making complex analytics feel simple. Whether it's automation, infrastructure, or insights, I focus on solutions that actually get used.
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