Data Engineering Podcast
This show goes behind the scenes for the tools, techniques, and difficulties associated with the discipline of data engineering. Databases, workflows, automation, and data manipulation are just some of the topics that you will find here.
Poslednja epizoda
Your Data, Your Lake: How Observe Uses Iceberg and Streaming ETL for Observability (19.01.2026)
Prethodne epizode
- Semantic Operators Meet Dataframes: Building Context for Agents with FENIC
- Beyond Dashboards: How Data Teams Earn a Seat at the Table
- Unfreezing The Data Lake: The Future-Proof File Format
- From Context to Semantics: How Metadata Powers Agentic AI
- From Data Engineering to AI Engineering: Where the Lines Blur
- Malloy: Hierarchical Data, Semantic Models, and the Future of Analytics
- Blurring Lines: Data, AI, and the New Playbook for Team Velocity
- State, Scale, and Signals: Rethinking Orchestration with Durable Execution
- The AI Data Paradox: High Trust in Models, Low Trust in Data
- Bridging the AI–Data Gap: Collect, Curate, Serve
- Beyond the Perimeter: Practical Patterns for Fine‑Grained Data Access
- The True Costs of Legacy Systems: Technical Debt, Risk, and Exit Strategies
- Context Engineering as a Discipline: Building Governed AI Analytics
- The Data Model That Captures Your Business: Metric Trees Explained
- From GPUs-as-a-Service to Workloads-as-a-Service: Flex AI’s Path to High-Utilization AI Infra
- From RAG to Relational: How Agentic Patterns Are Reshaping Data Architecture
- Duck Lake: Simplifying the Lakehouse Ecosystem
- Aligning Business and Data: The Essential Role of Data Modeling
- From Academia to Industry: Bridging Data Engineering Challenges
- High Performance And Low Overhead Graphs With KuzuDB
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