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.DS_Store (12292, 2023-02-19)
02-20-2022/ (0, 2023-02-19)
02-20-2022/hifly-labs.yaml (368, 2023-02-19)
05-12-2022 (288, 2023-02-19)
05-15-2022/ (0, 2023-02-19)
05-15-2022/rovio-entertainment-corporation.yaml (495, 2023-02-19)
05-29-2022/ (0, 2023-02-19)
05-29-2022/dewitt-clause-or-can-you-benchmark-a-database.yml (514, 2023-02-19)
07-17-2022/ (0, 2023-02-19)
07-17-2022/spark-streaming-as-a-service.yml (496, 2023-02-19)
08-21-2022/ (0, 2023-02-19)
08-21-2022/know-your-limits-cluster-benchmarks.yml (322, 2023-02-19)
09-11-2022 (391, 2023-02-19)
20-02-2023/ (0, 2023-02-19)
20-02-2023/benchmarks-bigquery-spark-dataflow.yml (634, 2023-02-19)
LICENSE (11357, 2023-02-19)
data_engineering_weekly_34.json (6060, 2023-02-19)
data_engineering_weekly_35.json (6546, 2023-02-19)
data_engineering_weekly_36.json (7817, 2023-02-19)
data_engineering_weekly_37.json (6393, 2023-02-19)
data_engineering_weekly_38.json (5441, 2023-02-19)
data_engineering_weekly_39.json (5187, 2023-02-19)
data_engineering_weekly_40.json (4691, 2023-02-19)
data_engineering_weekly_41.json (6888, 2023-02-19)
data_engineering_weekly_42.json (6175, 2023-02-19)
data_engineering_weekly_43.json (5875, 2023-02-19)
data_engineering_weekly_44.json (6912, 2023-02-19)
data_engineering_weekly_45.json (6613, 2023-02-19)
data_engineering_weekly_46.json (4814, 2023-02-19)
data_engineering_weekly_47.json (5674, 2023-02-19)
data_engineering_weekly_48.json (6140, 2023-02-19)
data_engineering_weekly_49.json (6591, 2023-02-19)
data_engineering_weekly_50.json (4839, 2023-02-19)
data_engineering_weekly_51.json (4728, 2023-02-19)
data_engineering_weekly_52.json (4050, 2023-02-19)
data_engineering_weekly_53.json (5316, 2023-02-19)
data_engineering_weekly_54.json (5701, 2023-02-19)
data_engineering_weekly_55.json (5981, 2023-02-19)
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# Data Engineering Weekly Weekly Data Engineering Newsletter The data engineering weekly newsletter started with a mission of reflecting views on the latest developments in the data engineering world. Every week we publish selected blog posts in the newsletters and share thoughts on them. Data Engineering Weekly currently accepts contributions in two forms. 1. Founder story. See the announcement for the [founder story](https://www.dataengineeringweekly.com/p/launching-the-data-founder-story). 2. Article contribution. # how can I contribute founder story The founder's story will be published every Wednesday as a separate edition. 1. Write your story with a title and one-pager or add a link to the blog post you already published your story. The markdown format is a preferred format. 2. Add the file under the founder_story folder, and open a PR. 3. You could also point to a blog post you already published, given that the data engineering weekly can republish the content. # how can I contribute articles? It is simple, open a pull request with the article title under the weekly folder. Please read the contributing guidelines before submitting the request. ```yaml article: author: linkedin: "" name: "" twitter: "" link: "" review: ". It is okay if you can just share the links to the articles." reviewer: linkedin: "" name: " if you would like to add your name as a reviewer in the data engineering weekly newsletter" twitter: "" tags: "" ``` Once the article submitted, the content will be either accepted or rejected for the publication. # Contributing Guide On average, we read about 15+ articles every week before selecting a few articles to publish in every edition. We focus more on the quality of the content rather than the quantity of the content. A few guidelines to follow for submitting the articles. 1. No vendor promotional articles. We want to keep the data engineering weekly vendor neutral, genuinely reflecting the exciting development in data engineering. 2. Practice empathy when writing the review snapshot. The author of the article spends tremendous time and effort to write the article. Positive feedback is welcome, but no negative comments/ criticism, please. 3. Data Engineering Weekly can accept or reject any article submission request without any further explanation. 4. The contribution is purely voluntary with no monetary benefit from data engineering weekly publishers. ### Note: I'm starting this as an experiment. The contributing guide may not be perfect. We will iterate and improve the contributing guideline as we move along. Please tag your suggestion [@data_weekly](https://twitter.com/data_weekly) on Twitter.

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