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SF Data Weekly - Visualizing Nothing, Visualizing Tile Grids and Remaking Ads

August 7 · Issue #149 · View online
SF Data Weekly
Our pick this week is much ado about nothing - the null, to be more precise. It includes some unique visualizations of the empty places that you may want to apply to your data analysis challenges. There’s also an interesting piece about chloropleths versus grid maps, and a deep dive into Twitter’s ad infrastructure. Stay healthy!

Our Pick
Visualizing the Nothing. How to visualize the incompleteness of… | by Thiago Carvalho | Aug, 2020 | Towards Data Science
Data Pipelines
New Relic drinks straight from the Firehose: Consuming Amazon Kinesis data | Amazon Web Services
Migrating a 40TB SQL Server Database - Taryn Pratt
Build a distributed big data reconciliation engine using Amazon EMR and Amazon Athena | Amazon Web Services
Get started with BigQuery and dbt, the easy way | by Felipe Hoffa | Jul, 2020 | Towards Data Science
Data Storage
BigQuery Cost and Performance Optimization | by Manas Pant | The Startup | Jul, 2020 | Medium
Apache Cassandra — Distributed Row-Partitioned Database for Structured and Semi-Structured Data | by Munish Goyal | The Innovation | Jul, 2020 | Medium
Data Analysis
What I understood by analyzing WhatsApp chats | by Reuben Joseph | Jul, 2020 | Towards Data Science
Data Visualization
Tile Narrative: Scrollytelling with Grid Maps | by Pratap Vardhan | Nightingale | Aug, 2020 | Medium
How to Draw Venn Diagrams on Jupyter | by Shinichi Okada | Jul, 2020 | Towards Data Science
Data-driven Products
Accelerating ad product development at Twitter
Data Engineering Jobs
Data Lead - Mozilla Foundation
Data Scientist - Stanford University School of Medicine
Intermix - build better data products with analytics into your data warehouse. Complete visibility into your data platform, who is touching your data, and how it’s being used.
Xplenty. - the leading data integration platform to bring all your data sources together. Trusted by companies like Gap, Samsung, Ikea, and Masterclass for their data pipelines.
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