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| October 15 · Issue #211 · View online |
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This week’s pick is a humorous data visualization of the experiences a new mum faces, including tears, tummy time and advice. We also have a piece on multiprocessing to speed up BigQuery data retrieval, and deep dive into Weatherbug’s use of Spectrum to decrease ETL latency. Stay Healthy!
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How I Survived Being a New Mum Using My Dataviz Goggles | Nightingale
When the author found out she was pregnant in the middle of the first lockdown, she decided to use a data-driven approach to document her pregnancy and early motherhood.
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BigQuery fetching + multiprocessing | by Tristan Bilot | Oct, 2021 | Towards Data Science
Benchmarking different approaches to fetching data using multiple threads, on a laptop and on a GCP compute engine.
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The fastest real-time data replication on the market | FlyData
FlyData has the fasted change data capture (CDC) on the market. Get real time data insights and updates so you don’t miss important changes to your data. [Sponsored]
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How To Build a Robust Data Infrastructure | *instinctools
A basic high-level summary describing five must-dos for creating an infrastructure that allows analysts easy access to your data.
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Automate your Amazon Redshift performance tuning with automatic table optimization | Amazon Web Services
An example with benchmarks showing how automatic distribution keys and sortkeys can make your Redshift tables perform without manual intervention.
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Why You Should Rethink Where You Write Your SQL | by Robert Yi | Oct, 2021 | Towards Data Science
“Where there once was only a thin trail of Slack whispers leading to an obscure Google doc, there now stands an almanac of past SQL queries, insights, and resulting business decisions.”
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Understanding Python imports, __init__.py and pythonpath — once and for all | by Dr. Varshita Sher | Oct, 2021 | Towards Data Science
A clear, example-based explanation of the workings of Python imports.
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Big Data Visualization Using Datashader in Python | by Sophia Yang | Oct, 2021 | Towards Data Science
Four lines of code and six milliseconds to plot 11 million rows of data on a laptop, with Datashader.
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Visualize data on a Choropleth map with Geopandas and Matplotlib | by Aindriya Barua (She/They) | Oct, 2021 | Medium
A nice example that plots the knowledge of English in India on a map.
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WeatherBug reduced ETL latency to 30 times faster using Amazon Redshift Spectrum | Amazon Web Services
Instead of using a Hadoop/Airflow transform, the WeatherBug team stored data directly in S3 for a striking increase in data pipeline performance.
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