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| December 17 · Issue #220 · View online |
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This week’s pick is a look at using the Agile methodology for analytics. We also have pieces on Scala at Databricks, identifying bird calls with Python, and why hiring a poet might be a smart move for your data visualization team. SF Data is taking a short holiday break and we’ll be back in 2022. Stay Healthy!
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How to make agile actually work for analytics | by Taylor Brownlow | Dec, 2021 | Towards Data Science
Going back to the original spirit of Agile to explain how you can make it work for analytics projects.
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Use unsupervised training with K-means clustering in Amazon Redshift ML | Amazon Web Services
Amazon Redshift ML allows users to create, train and deploy ML models using SQL commands. This piece presents a step-by-step showing how to get started with Redshift ML.
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Integrate.io Launch Event | Jan 27th, 2022 | Xplenty
A world-changing product is on the way. Changing the way e-commerce companies power their business with data integration.
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Top Google Cloud infrastructure blogs of 2021 | Google Cloud Blog
This year’s top posts in case you missed some big Google Cloud news.
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Scoring Customer Propensity using Machine Learning Models on Google Analytics Data | by Antoine Aubay | Artefact Engineering and Data Science | Dec, 2021 | Medium
Antoine built a model based on Google Analytics data that that increased the return on ad spend by 221% over a rule-based model and 73% over off-the-shelf ML.
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Hey, You! What’s that Bird?. The question both Skee-Lo and Buffalo… | by aarroonn | Digital-Futures-Publications | Dec, 2021 | Medium
Using Python with a Kaggle dataset of bird sounds to build a ML model to recognize bird calls.
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D3 and Data Visualization Insights with Mike Bostock
Mike Bostock, the creator of D3 shares the reasons for his data visualization tool’s longevity, and why it won the 10-year Test-of-Time award from the IEEE. Mike goes deep on D3 and Observable, which he also founded.
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Why can the quality of data visualization make or break your project? | by Lazar Glumac | Dec, 2021 | Holographik
Choosing the right visualization pattern, checking all the necessary boxes and creating a unique solution that’s still in line with the project you are working on is hard, and it takes tons of practice, iterations and time to do it accurately and effectively.
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A Poet’s Perspective: Seven Reasons Why Your Dataviz Team Should Include an Analyst from the Humanities | Nightingale
Looking beyond STEM degrees for members of a data visualization team.
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Scala at Scale at Databricks - The Databricks Blog
Learn more about everything big and small that goes into making Scala at Databricks work, from its inception and usage to style, tooling and the problems they faced – a useful case study for anyone supporting the use of Scala in a growing organization.
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Spotlighting scientists in the Lyft Kyiv office | by Sha Lu | Dec, 2021 | Lyft Engineering
The stories of two data scientists working for Lyft in Kyiv.
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