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SF Data Weekly - Visualizing Oscars, Faker and Data Cavities

April 8 · Issue #234 · View online
SF Data Weekly
This week’s pick is a visualization of 50 years of the Oscars - don’t worry, no slaps involved.
We also have test data creation with the Faker Python library, and ten recommended processes to find data cavities at scale. Stay healthy!

Our Pick
50 Years of Oscars: Acting Success and Collaboration | Nightingale
Data Pipelines
Build data lineage for data lakes using AWS Glue, Amazon Neptune, and Spline | Amazon Web Services
The Ultimate Guide to E-commerce Integrations |
Data Storage
Anomaly Detection in SQL. How to implement fast, powerful… | by Avi Chad-Friedman | Mar, 2022 | Towards Data Science
Data Analysis
You Don’t Need Sample Data, You Need Python Faker | by Christopher Tao | Mar, 2022 | Towards Data Science
No magical toothpaste for data quality cavities | by Sandeep Uttamchandani | Apr, 2022 | Towards Data Science
Data Visualization
A Simple Guide to Machine Learning Visualisations | by Rebecca Vickery | Mar, 2022 | Towards Data Science
Data-driven Products
Detecting silent errors in the wild: Combining two novel approaches to quickly detect silent data corruptions at scale - Engineering at Meta
How LyftLearn Democratizes Distributed Compute through Kubernetes Spark and Fugue | by Han Wang | Apr, 2022 | Lyft Engineering
Data Engineering Jobs
Traverse | Data Science Roadmap
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