SF Data Weekly - Data Governance, Catalogs and Great Expectations

#217・
5.24K

subscribers

259

issues

Subscribe to our newsletter

By subscribing, you agree with Revue’s Terms of Service and Privacy Policy and understand that SF Data Weekly will receive your email address.

Revue
 
 
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
Did you enjoy this issue?
In order to unsubscribe, click here.
If you were forwarded this newsletter and you like it, you can subscribe here.
Powered by Revue
650 California St., San Francisco, CA 94108