This week's pick is a comprehensive visualization of different data visualization libraries. We also
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October 2 · Issue #157 · View online |
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This week’s pick is a comprehensive visualization of different data visualization libraries. We also have some experience-based pieces on using Spark and Databricks, as well as Snowflake implementation tips. Stay healthy!
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Navigating the Wide World of Data Visualization Libraries | by Krist Wongsuphasawat | Nightingale | Sep, 2020 | Medium | Nightingale
Graphics and visualization developers often get presented with a simple yet difficult question: “Which visualization library should I use?” This piece includes examples, well-executed comparison grid ranking libraries on level of abstraction and API design, and some brief code examples.
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Spark & Databricks: Important Lessons from My First Six Months | by Daniel Harrington | Sep, 2020 | Towards Data Science
A deep look at two sometimes confusing Spark features: DataFrames and lazy evaluations.
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Best practices using AWS SCT and AWS Snowball to migrate from Teradata to Amazon Redshift | Amazon Web Services
How ZS, an AWS consultancy, migrated a client from an on premises Teradata database to Redshift, using AWS Schema Conversion Tool (SCT) for schema migration, and AWS Snowball for data migration.
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The top four things to get right when implementing Snowflake | by David Oyegoke | Slalom Data & Analytics | Sep, 2020 | Medium
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Exploratory Data Analysis (EDA) on Satellite Imagery Using EarthPy | by Syam Kakarla | Sep, 2020 | Towards Data Science
A deep dive into using EarthPy to plot and work with spatial raster and vector data, with code examples using openly available Landsat data.
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Time Series Forecasting With SQL — It’s Easier Than You Think | by Dario Radečić | Sep, 2020 | Towards Data Science
Time series forecasting is a often done in Python, R or Julia, but that doesn’t mean that good old SQL can’t get the job done, and this piece provides an example of how to train a model with pure SQL.
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How to Plan and Organize a Data Science Project? | by Yin Zhang | Towards Data Science
How to better understand the requirements and plan accordingly? How to organize and track the progress? What’s the framework to document your project? This piece gets into the soft skills needed to pull off a successful data science project, and it’s applicable to many more use cases.
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Want Some Bubbles With Your Donut…Chart? | by headonkeyboard | The Startup | Sep, 2020 | Medium
See how to combine a Donut Chart with a Bubble Chart and get the best of both worlds to create Bubble Donut Chart.
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Introducing visx from Airbnb. A collection of expressive, low-level… | by Chris C Williams | Airbnb Engineering & Data Science | Sep, 2020 | Medium
The visx project is a collection of data visualization primitives written in Typescript for React. Airbnb has just released version 1.0 as an open source project, and this piece reviews the different primitives with examples.
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Meet your 2020 ArcGIS StoryMaps Competition judges at the Storytelling for the SDGs webinar
This year’s ArcGIS StoryMaps competition is a collaboration between Esri and the United Nations Sustainable Development Solutions Network. Participants in the competition will create a story that addresses one or more Sustainable Development Goals (SDGs). This article introduces the judges and has a link to join an informational webinar.
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ETL made easier with Xplenty
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Xplenty Platform Demo: Extracting and Transforming Data with Teri Morgan
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Xplenty is an ETL solution with a visual interface that accelerates the ETL process. This demo shows extracting e-commerce order data, calling a foreign exchange API during the pipeline to get FX rates for currency localization, and then loading the enhanced order data into Snowflake.
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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.
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