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SF Data Weekly - 12 Days of Projects and Mythbusting Analytics at Netflix

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December 23 · Issue #169 · View online
SF Data Weekly
Even for those who don’t celebrate Christmas, the end of the year is a time to wind down and experiment with new projects, and our pick has one project for every one of the 12 days of Christmas.
We also have an interesting piece on FanDuel’s data architecture, and a piece that busts some myths about doing analytics for Netflix. Stay Healthy!

Our Pick
12 Data Science Projects for 12 Days of Christmas | by Terence Shin | Dec, 2020 | Towards Data Science
Data Pipelines
Setting up automated data quality workflows and alerts using AWS Glue DataBrew and AWS Lambda | Amazon Web Services
Optimizing Your Data Strategy with Modern ETL
Data Storage
Investigate BigQuery slowness with Python and INFORMATION_SCHEMA | by Jay Syz | Dec, 2020 | Medium
Accelerating Amazon Redshift federated query to Amazon Aurora MySQL with AWS CloudFormation | Amazon Web Services
Data Analysis
Ten awesome R Markdown tricks. R Markdown is more versatile than you… | by Keith McNulty | Dec, 2020 | Towards Data Science
A gentle Introduction to Bayesian Inference | by Dr. Robert Kübler | Dec, 2020 | Towards Data Science
Data Visualization
Our favorite stories of 2020
Animations of Gradient Descent and Loss Landscapes of Neural Networks in Python | by Tobias Roeschl | Dec, 2020 | Towards Data Science
Data-driven Products
How FanDuel Group secures personally identifiable information in a data lake using AWS Lake Formation | Amazon Web Services
Kafka as a storage system
Data Engineering Jobs
Mythbusting the Analytics Journey | Netflix TechBlog
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