Joe Reis
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no series more than once — all 6 in the filters
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who talks about the same things
- Mikiko Bazeley6 talks
- Ryan Boyd11 talks
- Thomas in't Veld5 talks
- Scott Sosna5 talks
- Rui Machado4 talks
- Matthias Niehoff8 talks
| title | conference | date |
|---|---|---|
| Mixed Model Arts | DataEngBytes Auckland 2024 | 2024-10-04 |
Argues that application, analytics and ML modeling must converge because siloed models and messy upstream data break AI projects — industry failure rates hover… | ||
| DataEngBytes 2023 - MEL-T1-01 - Joe Reis | DataEngBytes Melbourne 2023 | 2023-08-31 |
Argues that DATA MODELLING IS DEAD! LONG LIVE DATA MODELLING! but actually data modelling is critical for reliable AI, citing concrete problems like reactive… | ||
| 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… | ||
| Panel Discussion | DataEngBytes Melbourne 2023 | 2023-08-31 |
Panelists argue that tooling is transient so prioritize the data and model life cycle over specific libraries; treat LLM deployments as ML problems with… | ||
| DataEngBytes 2023 - BRI-T1-07 - Joe Reis | DataEngBytes Brisbane 2023 | 2023-08-29 |
Argues that data modeling is both abandoned and indispensable for AI, citing a real-world symptom of 39,000 DBT models in one company and widespread ad hoc… | ||
| 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… | ||
| DATA MODELLING IS DEAD! LONG LIVE DATA MODELLING! | DataEngBytes Sydney 2023 | 2023-08-25 |
Claims that data modelling is both neglected and essential for AI success, arguing that ignoring conceptual and logical modeling leads to brittle systems… | ||
| Panel Discussion | DataEngBytes Perth 2023 | 2023-08-22 |
Panel explores practical pain and fixes: thousands of messy models (about 8,000 dbt models at one company, a cited case of 39,000 dbt models) driving cost and… | ||
| Data Engineering in a Rapidly Changing World | DataEngBytes 2022 | 2022-09-27 |
Defines data engineering as managing the data engineering lifecycle: ingesting from systems, transforming, storing and serving for analytics or ML, not tool… | ||
| Panel discussion - Melbourne | DataEngBytes 2022 | 2022-09-27 |
Panelists report real outcomes: a production lake house in production ~1 year offloads Redshift and lets ML jobs read from S3 without impacting BI, an… | ||
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