Throughout the week, I read a lot of blog-posts, articles, and so forth, that has to do with things that interest me:
- data science
- data in general
- distributed computing
- SQL Server
- transactions (both db as well as non db)
- and other “stuff”
This blog-post is the “roundup” of the things that have been most interesting to me, for the week just ending.
Data Science
- Forecasting Best Practices, from Microsoft. It is a long time since I have linked to something from Revolution Analytics. That is now rectified by this post where David points to resources from Microsoft around best practices around time series forecasting. Have a look, quite a lot of cool stuff there!
- Rendezvous Architecture for Data Science in Production. In this post the author discusses one of the biggest problems in Data Science today how to productionise your models. The answer to that problem is something called the Rendezvous Architecture.
Distributed Computing
- Better design, implementation, and testing of async systems with Coyote. In the Interesting Stuff - Week 13, 2020 I wrote about Coyote, the framework for building reliable asynchronous software. The link here is a registration page for a webinar April 30 about Coyote. If you are interested in things like async and distributed systems, then I suggest you register. See you there!
Event Driven Architecture
- Event-Driven Data Collection. I linked to some posts about Event Driven Architecture in the Interesting Stuff - Week 14, 2020 post, and the post linked to here is by the same author as the posts in the week 14 roundup. In this post, the author discusses how to populate databases from event-driven data collection.
Streaming
- What’s New in Apache Kafka 2.5. Apache Kafka version 2.5 was released earlier this week, and the post here discusses new “stuff” in the release.
- Real-Time Small Business Intelligence with ksqlDB. In this post, the author makes the point that the Kafka ecosystem is not only for the Netflix:es in this world, but that by using ksqlDB even smaller companies can gain insights into their data.
- A quick and dirty way to monitor data arriving on Kafka. The title of this post describes the post perfectly. Robin Moffat shows a way to quickly and easily monitor Kafka data, and be alerted if something happens. Actually be alerted if something does not happen (data arriving).
~ Finally
That’s all for this week. I hope you enjoy what I did put together. If you have ideas for what to cover, please comment on this post or ping me. Most importantly, stay safe out there!
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