SF Data Weekly - Data Governance, Catalogs and Great Expectations





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November 26 · Issue #217 · View online
SF Data Weekly
This week’s pick is a look at data governance, why it got a bad name, and how to save its reputation.
We also have a piece on data catalog choice, as well as data integrity using Great Expectations. Stay Healthy!

Our Pick
Data Governance Has a Serious Branding Problem | by Prukalpa | Nov, 2021 | Towards Data Science
Data Pipelines
Provide data reliability in Amazon Redshift at scale using Great Expectations library | Amazon Web Services
How to create a Salesforce ETL pipeline in less than 30 minutes | Xplenty
Data Storage
Use the Amazon Redshift SQLAlchemy dialect to interact with Amazon Redshift | Amazon Web Services
How to evaluate a data catalog. The data catalog is becoming a… | by Grant Seward | Nov, 2021 | Medium
Data Analysis
An introduction to Probability Sampling Methods | by Eugenia Anello | Nov, 2021 | Towards Data Science
Use Cloud Storage as a mounted local file system in Vertex AI and AI Platform to store the training data and outputs. | Google Cloud Blog
Data Visualization
Visualising Global Population Datasets with Python | by Parvathy Krishnan | Nov, 2021 | Towards Data Science
5 Steps To Choosing Great Data Visualizations for Your Data Science Projects | by Benjamin Nweke | Nov, 2021 | Towards Data Science
Data-driven Products
The Rise (and Lessons Learned) of ML Models to Personalize Content on Home (Part II) : Spotify Engineering
Parameter Exploration at Lyft. What is Parameter Exploration | by Henry Quan | Nov, 2021 | Lyft Engineering
Data Engineering Jobs
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