Ryan Boyd
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who talks about the same things
- Hannes Mühleisen19 talks
- Jordan Tigani7 talks
- Gabor Szarnyas16 talks
- Manju Anand3 talks
- Matthias Niehoff8 talks
- Joe Reis16 talks
| title | conference | date |
|---|---|---|
| LLMs & Data Warehouses: Reliable AI Agents for Business (Keynote) | AI By the Bay 2025 | 2025-11-17 |
LLMs often hallucinate and fail at data aggregation so the talk demonstrates concrete fixes: use semantic models or commented views, feed a DuckDB/MotherDuck… | ||
| From Big Data to DuckDB: Ryan Boyd (MotherDuck) on Hyper-Tenancy, Duck Lake, and Making Data Fun. | AI By the Bay 2025 | 2025-11-17 |
Argues that replacing massive distributed engines with many small DuckDB instances yields real wins: MotherDuck’s hyper-tenancy gives each customer or user a… | ||
| Data infrastructure to build bigger with less | ODSC West 2024 | 2024-10-29 |
Argues that most analytics no longer need clusters by showing concrete results: DuckDB runs in-browser via WebAssembly and on laptops, a 13 billion‑row… | ||
| DataEngBytes 2023 - MEL-T1-07 - Ryan Boyd | DataEngBytes Melbourne 2023 | 2023-08-31 |
Argument for replacing monolithic cloud warehouses with a hybrid local+cloud model that actually runs: a 20‑MB in‑process SQL OLAP engine (DuckDB) embeds in… | ||
| Panel Discussion | DataEngBytes Melbourne 2023 | 2023-08-31 |
Debate over when to add guardrails gives concrete rules: treat data contracts as codified APIs (schema, SLAs, ownership) when data is a product; delay heavy… | ||
| DataEngBytes 2023 - BRI-T1-08 - Ryan Boyd | DataEngBytes Brisbane 2023 | 2023-08-29 |
Argues cloud warehouses act like modern mainframes and demonstrates a hybrid pattern using DuckDB locally (WASM, Python) with MotherDuck coordinating cloud… | ||
| Panel Discussion | DataEngBytes Brisbane 2023 | 2023-08-29 |
Argues data engineering expands beyond pipelines into data modeling and ongoing quality work, with concrete ML pitfalls like target leakage and distribution… | ||
| Panel Discussion | DataEngBytes Sydney 2023 | 2023-08-25 |
Panelists argue concrete tradeoffs: EDB claims it contributes over 30% of Postgres code annually, Postgres remains a solid default but not ideal for >10TB… | ||
| DataEngBytes 2023 - SYD-T1-01 - Ryan Boyd | DataEngBytes Sydney 2023 | 2023-08-25 |
Argues that true “big data” is rare: 95% of BigQuery customers have <1TB and 90% of queries touch <100MB, so distributed clusters are often overkill… | ||
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