According to the news, Tesla engineers visit Twitter for code reviews.

Useful Python library for data validation that has Rust based core.
https://pydantic-docs.helpmanual.io/

EP31: Super High-performance NoSQL and MQ - by Alex Xu
https://blog.bytebytego.com/p/ep31-super-high-performance-nosql

End-to-end Machine Learning for Everyone - PostgresML
https://postgresml.org/

Currently I am reading Harari's Sapiens where he explains how the current economic system depends on growth and trust in the future. I think in IT it is really vivid. There are some good points in this analysis.

2003–2023: A Brief History of Big Data | by Furcy Pin | Nov, 2022 | Towards Data Science
https://towardsdatascience.com/2003-2023-a-brief-history-of-big-data-25712351a6bc

The Distributed Computing Manifesto | All Things Distributed
https://www.allthingsdistributed.com/2022/11/amazon-1998-distributed-computing-manifesto.html

Announcing the latest version of the AWS Well-Architected Data Analytics Lens | AWS Big Data Blog
https://aws.amazon.com/blogs/big-data/announcing-the-latest-version-of-the-aws-well-architected-data-analytics-lens/

Second Lex Fridman podcast with the creator of Python.

Take your first steps with Rust - Training | Microsoft Learn
https://learn.microsoft.com/en-us/training/paths/rust-first-steps/

🧵 on AWS reInvent 2022
https://twitter.com/TechCrunch/status/1597659047104483329?s=20&t=PU9xA-QdQAZozZVtqzO76A

Better late than never.
https://aws.amazon.com/about-aws/whats-new/2022/11/amazon-redshift-integration-apache-spark-amazon-emr/

AWS Glue announces AWS Glue Data Quality (Preview)
https://aws.amazon.com/about-aws/whats-new/2022/11/aws-glue-data-quality-preview/

Amazon Redshift now supports auto-copy from Amazon S3
https://aws.amazon.com/about-aws/whats-new/2022/11/amazon-redshift-supports-auto-copy-amazon-s3/

Blockchain is becoming quite a popular dataset type.

I decided to ask a ChatGPT following questions "What are the differences between Azure Synapse, Databricks, and Azure Data Explorer (Kusto)?" to compare with the review I wrote a while ago. Here is what I've got as an answer:

Azure Synapse, Databricks, and Azure Data Explorer (Kusto) are all Microsoft Azure services that are focused on data analytics and big data processing. While they have some similarities, there are also some key differences between the three.

Azure Synapse is a cloud-based data integration and analytics platform that combines enterprise data warehousing, big data integration and processing, and data integration and orchestration into a single platform. It is designed to help organizations quickly and easily integrate, process, and analyze large volumes of data from a wide range of sources.

Databricks is a cloud-based platform for data engineering, data science, and analytics. It is based on the open-source Apache Spark project, and it provides a managed environment for running Spark jobs, as well as tools for collaboration, data management, and machine learning.

Azure Data Explorer (Kusto) is a fast, highly scalable data exploration service that is optimized for log and time-series data. It is designed to help organizations quickly and easily analyze large volumes of data to gain insights and understand patterns and trends in their data.

Overall, each of these services has its own strengths and is suited to different use cases. Azure Synapse is a good choice for organizations that need a comprehensive data integration and analytics platform, while Databricks is a good choice for data engineering and data science workloads, and Azure Data Explorer is a good choice for analyzing log and time-series data.