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SF Data Weekly - Lots of Redshift and a Sense of Wonder

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Our pick this week goes back to the author's childhood to find examples of using physical objects to
 
December 18 · Issue #168 · View online
SF Data Weekly
Our pick this week goes back to the author’s childhood to find examples of using physical objects to help visualize data – hopefully, her experience will inspire you.
Our other, more traditional focus is Redshift. AWS is determined to enhance Redshift to keep up with the competition, and we have a slew of articles describing some really useful new features. Stay healthy!

Our Pick
How to Create Wonder with Data and a Physical Object | by Alli Torban | Nightingale | Dec, 2020 | Medium
Data Pipelines
Building SQL pipelines in BigQuery with Dataform | by Lak Lakshmanan | Google Cloud - Community | Dec, 2020 | Medium
Xplenty | Simplified ETL & ELT to BigQuery, Snowflake, Redshift & Azure
Data Storage
Optimizing tables in Amazon Redshift using Automatic Table Optimization | Amazon Web Services
Announcing Amazon Redshift data sharing (preview) | Amazon Web Services
Amazon Redshift announces support for native JSON and semi-structured data processing (preview)
Getting the most out of your analytics stack with Amazon Redshift | Amazon Web Services
Data Analysis
Data Generation and KPI Dashboarding with SQURL | by Trent Currie | Dec, 2020 | Medium
Data Visualization
Introducing Artemis: Deno’s First Analytics Tool for GraphQL Queries | by Stella Liao & Greg Dixon | Artemis-Project | Dec, 2020 | Medium | Artemis-Project
Interactive data visualization using Plotly and Cufflinks | by Jayashree domala | Dec, 2020 | Medium
Data-driven Products
Why We Disable Linux's THP Feature for Databases | PingCAP
No Code Workflow Orchestrator for Building Batch & Streaming Pipelines at Scale | Uber Engineering Blog
Data Engineering Jobs
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