Lars Albertsson
where else to find them
what they talk about
all 9 in the filters
where they keep going back
- Berlin Buzzwords6 editions2018–2025
- Jfokus3 editions2016–2022
- Øredev2 editions2019–2022
on a stage with
- Ellen Friedmanonce
who talks about the same things
- Arne Laponin4 talks
- Emily Gorcenski20 talks
- Matthias Niehoff8 talks
- Jesse Anderson15 talks
- David Ostrovsky20 talks
- Milos Milovanovic5 talks
| title | conference | date |
|---|---|---|
| All the DataOps, all the paradigms | Berlin Buzzwords 2025 | 2025-06-15 |
Choices between Hadoop, warehouses, lakes, streams and meshes change ops cost and iteration speed by orders of magnitude: a 2,000-node dependency graph… | ||
| End-to-end pipeline agility | Berlin Buzzwords 2024 | 2024-06-09 |
Quantitative claim: adapting downstream pipelines ranges from median 6 months to some teams doing it in less than a day, a gap of 100x–1000x. The setup uses… | ||
| How to not kill people | Berlin Buzzwords 2023 | 2023-06-18 |
Compares aviation safety to software and AI with concrete takeaways: aviation averages about 270 deaths per year and still treats every incident (Habsheim… | ||
| Data engineering in 10 years | Øredev 2022 | 2022-11-08 |
Predicts that data engineering industrializes into data factory engineering, moving from Hadoop and data lakes through the modern data stack and lakehouse to… | ||
| The 7 habits of data effective companies | Øredev 2022 | 2022-11-08 |
Argues that data efficiency shows order-of-magnitude gaps — a 1000x span in outcomes and even a 10000x cost example from Lego versus Mojang — and ties that to… | ||
| Secure software supply chain on a shoestring budget | Jfokus 2022 | 2022-05-02 |
The team industrializes supply-chain security by locking exact versions in a Bazel-based monorepo and automating safe upgrades with an automated dependency bot… | ||
| Data engineering & DataOps: Ask Me Anything | Berlin Buzzwords 2021 | 2021-06-15 |
Built early video conferencing at Google and later a Spotify internal data platform that democratizes analytics, uses Hadoop-era patterns (immutable inputs… | ||
| Engineering data quality | Øredev 2019 | 2019-11-06 |
Argues that data quality is an engineering problem with concrete tactics: use Luigi or Airflow for orchestration, emit counters and invariants to monitor… | ||
| Eventually, time will kill your data processing | Øredev 2019 | 2019-11-06 |
Lists concrete failure modes — daylight savings, leap seconds, client clocks, late mobile events, and duplicated hours — and shows where they break data… | ||
| Eventually, time will kill your data pipeline | Berlin Buzzwords 2019 | 2019-06-16 |
Catalogues concrete failure modes (daylight saving causing silent hourly data loss, leap second spikes, time-zone offsets) and shows reproducible fixes: using… | ||
| Top 10 data engineering mistakes #bbuzz | Berlin Buzzwords 2018 | 2018-06-11 |
Pick a proper workflow orchestrator rather than ad hoc scripts—use Luigi or Airflow—so pipelines are reproducible and recoverable (typical rollback time with… | ||
| Privacy by design | Jfokus 2018 | 2018-02-05 |
Explains concrete engineering patterns to meet GDPR: use a workflow orchestrator so batch Spark/MapReduce pipelines can reprocess raw events and honor deletion… | ||
| Data pipelines from zero to solid | Jfokus 2016 | 2016-02-08 |
Recommendations and concrete practices for building reliable data pipelines: use Kafka unified log for ingestion, mirror to HDFS as an immutable data lake and… | ||
| Data pipelines | Jfokus 2016 | 2016-02-08 |
NightHacking interview at the Jfokus conference with Lars Albertsson on Data pipelines. | ||
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