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SF Data Weekly - A Theory of B.S. Visualization, Perfect Prefect and Nim

October 1 · Issue #209 · View online
SF Data Weekly
Our pick this week is what the author calls an “unhinged rant” about visualizations that look good but don’t tell you anything about the state of the world.
We also have perfect workflows using Prefect, and Nim instead of Python. Stay healthy!

Our Pick
Towards a Theory of B.S. Visualization | Tableau Research
Data Pipelines
Scaling Your Prefect Workflow to the Cloud | by Richard Pelgrim | Sep, 2021 | Towards Data Science
How to get real-time data insights to Amazon Redshift and Snowflake | FlyData
Data Storage
Comparing BigQuery Processing and Spark Dataproc | by Vignesh Raj K | The PayPal Technology Blog | Sep, 2021 | Medium
Creating a Metadata Architecture From the Ground Up | by Marcelo Alves Baratela | QuintoAndar Tech Blog | Sep, 2021 | Medium
Data Analysis
Make Python Faster with CFFI Python Bindings | by Dimitris Poulopoulos | Sep, 2021 | Towards Data Science
Why I Use Nim instead of Python for Data Processing :: Benjamin D. Lee — Research Software Engineer
Data Visualization
How to Iterate on a CDC Health Advisory Graphic | Nightingale
Data Visualization Has a Taxonomy Problem | by Elijah Meeks | Noteable | Sep, 2021 | Medium
Data-driven Products
How Airbnb Enables Consistent Data Consumption at Scale | by Shao Xie | The Airbnb Tech Blog | Sep, 2021 | Medium
How NortonLifelock built a serverless architecture for real-time analysis of their VPN usage metrics | Amazon Web Services
Data Engineering Jobs
Data Engineer - Meritage Medical Network
BI Developer - American AgCredit
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