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November 12 · Issue #215 · View online |
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Our pick this week has three examples of automating those little tasks that, taken individually, are easy, but add up over time. We also have a piece on the Python Prefect workflow automation library, and the Pendulum time library, as well as a real-world example of how visualization helped activists understand the impact of Airbnb. Stay Healthy!
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3 Python Projects That Will Help Automate Your Life | by Frank Andrade | Nov, 2021 | Towards Data Science
Using mitosheet and selenium to automate repetitive tasks like creating spreadsheets and graphs, and scraping data from websites.
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Orchestrate a Data Science Project in Python With Prefect | by Khuyen Tran | Nov, 2021 | Towards Data Science
How to break your workflow into chunks with Prefect, automatically.
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How to get real-time data insights to Amazon Redshift or Snowflake | FlyData
Real-time data replication is needed by many idustries including: eCommerce, Fintech, Healthcare, and SaaS. If you need real-time data insights, FlyData could be a good solution. [Sponsored]
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Query hierarchical data models within Amazon Redshift | Amazon Web Services
Hierarchical databases are useful when you need to represent data in a tree-like hierarchy, and Redshift’s recently introduced Common Table Expressions (CTEs) can help make querying hierarchical tables easier and faster.
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Choosing a network connectivity option in Google Cloud | Google Cloud Blog
Google offers four different ways to connect to their offerings. This piece helps you decide which one is right for your application.
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All Machine Learning Algorithms You Should Know in 2022 | by Terence Shin | Nov, 2021 | Towards Data Science
A look at of the most important types of ML algorithms.
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Pendulum: Probably The Best Python DateTime Library | by Christopher Tao | Nov, 2021 | Towards Data Science
Pendulum is a drop-in replacement for the standard Python datetime library that resolves the issues that the standard library has with timezones, for example.
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I’ve Stopped Using Box Plots. Should You? | Nightingale
After having explained how to read box plots to thousands of workshop participants, the author now believes that they’re poorly conceived and prone to misinterpretation.
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What Data Visualization and Analysis Taught One Activist about Airbnb’s Impact on Communities | Nightingale
Activist and technologist Murray Cox has been described as a “Lone Data Whiz” who is Airbnb’s “Public Enemy No. 1 in New York.“ This piece describes how his project, Inside Airbnb, became a key tool for housing advocates in New York City.
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Forecasting SQL query resource usage with machine learning
How Twitter engineers apply machine learning techniques to forecast SQL query resource utilization during the development and maintenance of our large-scale SQL system.
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TrueBlue uses Amazon QuickSight to deliver more accurate pricing and grow business | Amazon Web Services
TrueBlue, a staffing company, uses QuickSight to provide regional pricing data to its sales team.
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