Data Quality Implementation in Data Warehouses | Toptal
https://www.toptal.com/database/data-warehouse-data-quality-process?utm_campaign=Toptal%20Engineering%20Blog&utm_medium=email&_hsmi=94506066&_hsenc=p2ANqtz-96vNKU-BhpAA5fMC-8gJ3pDBq23ob6VF1lvqOxgYVoATaLUYMQexXEDzJN9c-dFoeH5APIz07aa8hrA2PL9wlSXo1PA62qBFqdkzcTTTOV4AIoWbE&utm_content=94506066&utm_source=hs_email
https://www.toptal.com/database/data-warehouse-data-quality-process?utm_campaign=Toptal%20Engineering%20Blog&utm_medium=email&_hsmi=94506066&_hsenc=p2ANqtz-96vNKU-BhpAA5fMC-8gJ3pDBq23ob6VF1lvqOxgYVoATaLUYMQexXEDzJN9c-dFoeH5APIz07aa8hrA2PL9wlSXo1PA62qBFqdkzcTTTOV4AIoWbE&utm_content=94506066&utm_source=hs_email
Toptal Engineering Blog
Data Quality Implementation in Data Warehouses
Data quality is a crucial element of any successful data warehouse solution. As the complexity of data warehouses increases, so does the need for data quality processes.
Very useful and relevant blog post about data deletion in a data lake. Besides suggested solution I would like to mention also using Delta Lake as alternative. And finally, it would be great if the author has mentioned cost considerations .
https://aws.amazon.com/blogs/big-data/how-to-delete-user-data-in-an-aws-data-lake/
https://aws.amazon.com/blogs/big-data/how-to-delete-user-data-in-an-aws-data-lake/
Amazon
How to delete user data in an AWS data lake | Amazon Web Services
General Data Protection Regulation (GDPR) is an important aspect of today’s technology world, and processing data in compliance with GDPR is a necessity for those who implement solutions within the AWS public cloud. One article of GDPR is the “right to erasure”…
Amazing statistics about data.
https://www.datanami.com/2020/09/04/10-big-data-statistics-that-will-blow-your-mind/?utm_source=rss&utm_medium=rss&utm_campaign=10-big-data-statistics-that-will-blow-your-mind
https://www.datanami.com/2020/09/04/10-big-data-statistics-that-will-blow-your-mind/?utm_source=rss&utm_medium=rss&utm_campaign=10-big-data-statistics-that-will-blow-your-mind
Datanami
10 Big Data Statistics That Will Blow Your Mind
They call it “big data” for a reason--it's really, really big. But getting your head wrapped around the growth of information digitization is not easy.
20x improvement compared to #Spark 2.4
https://techcommunity.microsoft.com/t5/azure-databricks/turbocharge-azure-databricks-with-photon-powered-delta-engine/ba-p/1694929
https://techcommunity.microsoft.com/t5/azure-databricks/turbocharge-azure-databricks-with-photon-powered-delta-engine/ba-p/1694929
TECHCOMMUNITY.MICROSOFT.COM
Turbocharge Azure Databricks with Photon powered Delta Engine
Today we are excited to announce the preview of Photon powered Delta Engine on Azure Databricks – fast, easy, and collaborative Analytics and AI service. Built from scratch in C++ and fully compatible with Spark APIs, Photon is a vectorized query engine that…
Most of the subscribers know why I've paused posting in the channel. I think most of you are busy now with other important issues. So I would like to create a poll to ask you whether you would like to see new posts or not yet. Thank you for understanding.
Anonymous Poll
63%
Yes
37%
Not yet
#AWS released open-source Python connector for Redshift with Data API support. By the way Redshift Data API was also announced recently.
https://github.com/aws/amazon-redshift-python-driver
https://github.com/aws/amazon-redshift-python-driver
GitHub
GitHub - aws/amazon-redshift-python-driver: Redshift Python Connector. It supports Python Database API Specification v2.0.
Redshift Python Connector. It supports Python Database API Specification v2.0. - aws/amazon-redshift-python-driver
It seems that #AWS is improving #Redshift on a weekly basis. Here is another cool feature.
https://aws.amazon.com/about-aws/whats-new/2020/11/amazon-redshift-announces-automatic-refresh-and-query-rewrite-for-materialized-views/
https://aws.amazon.com/about-aws/whats-new/2020/11/amazon-redshift-announces-automatic-refresh-and-query-rewrite-for-materialized-views/
Amazon Web Services, Inc.
Amazon Redshift announces automatic refresh and query rewrite for materialized views
A comparison of data version control tools.
https://dagshub.com/blog/data-version-control-tools/
https://dagshub.com/blog/data-version-control-tools/
DagsHub Blog
Comparing Data Version Control Tools - 2020
Data versioning is one of the keys to automating a team's machine learning model development. While it can be very complicated if your team attempts to develop its own system to manage the process, this doesn’t need to be the case.
A short series of articles from Lyft about Gevent #Python library.
https://eng.lyft.com/what-the-heck-is-gevent-4e87db98a8
https://eng.lyft.com/gevent-part-2-correctness-22e3b7998382
https://eng.lyft.com/gevent-part-3-performance-e64303fa102b
https://eng.lyft.com/applying-gevent-learnings-to-deliver-value-to-users-part-4-of-4-36ad932deea8
https://eng.lyft.com/what-the-heck-is-gevent-4e87db98a8
https://eng.lyft.com/gevent-part-2-correctness-22e3b7998382
https://eng.lyft.com/gevent-part-3-performance-e64303fa102b
https://eng.lyft.com/applying-gevent-learnings-to-deliver-value-to-users-part-4-of-4-36ad932deea8
Medium
What the heck is gevent?
Overview
Introduction to Apache Pinot, a real-time distributed OLAP datastore from LinkedIn and Uber
https://docs.pinot.apache.org/
https://docs.pinot.apache.org/
docs.pinot.apache.org
Introduction | Apache Pinot Docs
Apache Pinot is a real-time distributed OLAP datastore purpose-built for low-latency, high-throughput analytics, and perfect for user-facing analytical workloads.
Some important updates from #AWS :
✅ Amazon Kinesis Data Streams enables data stream retention up to one year.
✅ Now you can export your Amazon DynamoDB table data to your data lake in Amazon S3 to perform analytics at any scale.
✅ Amazon Redshift now supports modifying column compression encodings to optimize storage utilization and query performance
✅ Amazon Athena announces availability of engine version 2
✅ Amazon Kinesis Data Streams enables data stream retention up to one year.
✅ Now you can export your Amazon DynamoDB table data to your data lake in Amazon S3 to perform analytics at any scale.
✅ Amazon Redshift now supports modifying column compression encodings to optimize storage utilization and query performance
✅ Amazon Athena announces availability of engine version 2
Amazon
Amazon Kinesis Data Streams enables data stream retention up to one year
➡️ Discover the new syntax for implicits in #Scala 3.
➡️ Learn how to express extension methods, implicit parameters, implicit conversions, and typeclasses in #Scala 3!
https://t.co/BYFnTVc3yh
➡️ Learn how to express extension methods, implicit parameters, implicit conversions, and typeclasses in #Scala 3!
https://t.co/BYFnTVc3yh
www.scala-lang.org
Explicit term inference with Scala 3
#AWS updates:
✅ Amazon EMR now provides up to 35% lower cost and up to 15% improved performance for Spark workloads on Graviton2-based instances
✅ AWS Glue Streaming ETL jobs support reading records in the Apache Avro format
✅ Control the evolution of data streams using the AWS Glue Schema Registry
✅ Amazon EMR now provides up to 35% lower cost and up to 15% improved performance for Spark workloads on Graviton2-based instances
✅ AWS Glue Streaming ETL jobs support reading records in the Apache Avro format
✅ Control the evolution of data streams using the AWS Glue Schema Registry
Amazon
Amazon EMR now provides up to 35% lower cost and up to 15% improved performance for Spark workloads on Graviton2-based instances