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SF Data Weekly - Data Artists, Sharding and Levenshtein Distance

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March 25 · Issue #232 · View online
SF Data Weekly
This week’s pick is an introduction to the data artist role at a grocery retailer.
We also have a piece explaining the performance benefits of sharding, as well as a Python implementation of the Levehshtein algorithm for plagarism detection. Stay healthy!

Our Pick
So what does a data artist in grocery retail work on? | by Cognetry Labs Inc. | Mar, 2022 | Medium
Data Pipelines
Accelerate your data warehouse migration to Amazon Redshift – Part 5 | Amazon Web Services
Magento2 vs. Shopify Plus: How to Choose the Right Ecommerce Platform | Integrate.io
Data Storage
How sharding a database can make it faster - Stack Overflow Blog
Data Mesh Architecture
A Fundamental Guide to SQL Query Optimization | by Koushik Thota | Mar, 2022 | Medium
Data Analysis
Data Sampling Methods in Python. A ready-to-run code with different data… | by Tatev Karen | Mar, 2022 | Towards Data Science
Text Similarity w/ Levenshtein Distance in Python | by Vatsal | Mar, 2022 | Towards Data Science
Data Visualization
How to use Color Palettes for your Data Visualization | by Dr. Gregor Scheithauer | Mar, 2022 | Towards Data Science
Who are the finalists of the 2022 Iron Viz Qualifiers?
Data-driven Products
How Beike built its Unified Metrics Platform using Apache Kylin | by Coco Li | Kyligence | Mar, 2022 | Medium
Graph machine learning with missing node features
Data Engineering Jobs
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