SF Data Weekly - Visualizing Mexican Food in NYC, Fanatics and Pandas for Big Data





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August 28 · Issue #152 · View online
SF Data Weekly
Our pick this month shows off the ArcGIS StoryMaps platform as well as delicious Mexican food, by tracing the growth of Mexican restaurants in New York City. Worth a click just to see the platform.
A deep dive into Fanatics data visualization architecture, and the use of Pandas with big data are two other highlights. Stay healthy!

Our Pick
The Mexican Restaurants of New York City
Data Pipelines
Debezium and KStreams to Handle Data Aggregation | by Adrian Eka Sanjaya | Aug, 2020 | Medium
Automate dataset monitoring in Amazon QuickSight | Amazon Web Services
Data Storage
How to do text similarity search and document clustering in BigQuery | by Lak Lakshmanan | Aug, 2020 | Towards Data Science
Speed up data ingestion on Amazon Redshift with BryteFlow | Amazon Web Services
Data Analysis
A Sudden Drop in User Engagement. Using product analytics, data… | by Jodi Zhang | Aug, 2020 | Towards Data Science
17 Strategies for Dealing with Data, Big Data, and Even Bigger Data | by Jeff Hale | Aug, 2020 | Towards Data Science
Data Visualization
How We Visualized a Data Set That Contains Many Messages | by Felix Buchholz | Nightingale | Aug, 2020 | Medium
Visualization Of COVID-19 New Cases Over Time In Python | by Jason Bowling | Aug, 2020 | Towards Data Science
Adventures with metrics in The Times and The Sunday Times newsrooms — Part 1: Problems | by Dan Gilbert | News UK Technology | Aug, 2020 | Medium
Data-driven Products
FanViz: Data visualization @ Fanatics | by Fanatics Tech Team | Fanatics Tech Blog | Aug, 2020 | Medium
Scale your cloud data warehouse and reduce costs with the new Amazon Redshift RA3 nodes with managed storage | Amazon Web Services
Data Engineering Jobs
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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