DAYMN — 15 Aug 2021
Data Articles You Might Need
I read a lot of informative and thought-provoking articles every week, and share them immediately in a piecemeal fashion, with friends and colleagues.
One, it is hard to find these articles again – when you need them – despite using a combination of Read-Later tools. And second, the nature of these fleeting shares are quite ephemeral making it hard to retain the insights in this age of information overload.
So, I thought it would be a better practice to batch and share the top 5 articles I read every week along with a short write-up on what was interesting in these articles.
Here are the top 5 articles from this past week — please do share your feedback & thoughts!
1. Future of Data Engineering:
Loved reading this article by RudderStack. Why? Data Engineering is a critical piece of every business and is one of the most hardest talents to attract and retain. With the growing commoditisation of standard services, event-driven architectures and more microservices based constructs, it is imperative to have Data Engineering as a service, and not as a team or a platform. This article talks a lot about the history and how we can get there!
https://rudderstack.medium.com/the-future-of-data-engineering-115f0772c9b6
Call out? Instead of asking “how can we use data to make this better,” teams are partnering with data engineering to ask, “how can our data and data systems shape the way we think about solving this problem.” Over the next 10 years, this strategic collaboration will be the standard in business operations and organisational structure.
2. Data Catalogs — The Evolution and 3.0:
Off late, ever since I started work for a regulated business who are keen on governing their data more rigorously, understanding and appreciating data catalogs has been on my radar. This article from Prukalpa does an amazing job of documenting the history from the MDM days to the new age Data Catalog 3.0. As someone who’s implementing an Aussie made data catalog tool, this is very exciting!
Call out? Instead, Data Catalog 3.0s will be built on the premise of embedded collaboration that is key in today’s modern workplace, borrowing principles from Github, Figma, Slack, Notion, Superhuman, and other modern tools that are commonplace today.
3. Reverse ETL Tools — Lay of the Land
We are all so busy building custom connectors from our source systems to our data lakes, that we forget or are spent, when the time comes to send data from our data lakes back to source systems to take some action. While I was researching to find an easy way to do it, I came across this quick primer from Astasia Myers on the world of Reverse ETL open-source tools and how they can help get this jack-knifed soon. I love open source and this was a great find for me.
https://medium.com/memory-leak/reverse-etl-a-primer-4e6694dcc7fb
4. Building an AI-first SaaS Product — The Napkin Approach:
As someone trying to build an AI-first SaaS product, this article from Louis Coppey was amazing food for thought on how to think about building such a product, where it stacks to the other products, what good looks like and how to think about growth of the product. Definitely a recommended reading, for those who are keen on understanding and building an AI-first SaaS product of your own. It’s a couple years old, but still relevant.
https://machinelearnings.co/the-ai-first-saas-funding-napkin-2cb138070ffc
5. Remote Work & Flexibility:
Novel concept from Google on providing flexible working arrangements for their staff — work from anywhere they want in the world for 4 weeks apart from the usual annual leaves. Great perk for people whose families and loved ones live in different countries. This policy aims to give people more options to better plan their vacations and holidays.
Have a wonderful week ahead everyone, hope at least one of these articles is exciting reading material for you, and made you think for a moment!
