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Ellen Friedman

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Data engineering & DataOps: Ask Me AnythingBerlin Buzzwords 20212021-06-15
Built early video conferencing at Google and later a Spotify internal data platform that democratizes analytics, uses Hadoop-era patterns (immutable inputs…
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Doing Data: The Critical Process of Data Preparation (...)Berlin Buzzwords 20192019-06-16
A practical playbook for making ML projects work: preserve raw inputs (one lab kept blood samples for 30 years and later found genetic signals), verify labels…
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Tales from the Field: The Future is NowJfokus 20192019-02-04
Emerging work shows machine learning’s payoff depends less on models and more on data logistics — about 90% of effort goes into preparing, versioning and…
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7 Successful Habits For Data-intensive Applications In ProductionBig Data LDN 20182018-11-28
Claims that MapR customers get >90% of large-scale projects into production vs Gartner's ~17% and explains why, with concrete practices: treat raw data as…
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Beyond the Algorithm: What Makes Machine Learning Work?Berlin Buzzwords 20182018-06-11
Anecdotes and case studies show the difference between a lab model and production value: a Raspberry Pi running a TensorFlow+Inception v3 classifier on…
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The Surprising Course of Knowledge and Innovation #bbuzzBerlin Buzzwords 20162016-06-05
Argues that disciplined measurement, record‑keeping and asking “what changed” beat vague theory: historical case shows Matthew Maury aggregates of ship logs…
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Talk the Talk: How to Communicate with the Non-Coder #bbuzzBerlin Buzzwords 20152015-05-31
Clear claim: technical teams must translate core ideas into concrete, testable messages for non-coders to get resources and domain input. Practical techniques…
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Time Series DatabasesStrata + Hadoop World Conference in Barcelona 20142014-11-19
The book Time Series Databases lays out how to collect and store high-volume sensor data, recommends NoSQL store patterns, and shows concrete designs and…
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