Just an illustration — not the truth and we will pivot if it does not work.

I discovered Zhamak Dehghani’s first article about Data Mesh in August 2020. Thanks to Youtube, you have the live illustration in this video with even more context and explanations. And then, you have this second video that is an introduction to her second article (december 2020). It is really a journey with a brillant person who has really a discovery mindset. She keeps making this concept better and clearer. …

“The right process will deliver the right results” — Totoya way (section II)

The agile part of DataOps

In a previous article, we have defined dataops as a ”combination of tools and methods inspired by Agile, Devops and Lean Manufacturing “ (thanks to DataKitchen for this definition).

Let’s focus on the agile part and why it is so relevant for your data use cases.

It is about the nature of data : you cannot guess what will be the content and the quality of your data sources before seing it. The Exploratory Data Analysis part is the starting point and you will have to adjust based on what you have found. Metrics or dimensions that you have specified…

(And why you should care having the right mix)

#1 : Possibly the integration or ESB team… totally focus on the technology and following the best software engineer standards. But they really do not care about the data itself. Apples, tomatoes or cars : everything same but in real time ^^

#2 : We know data (most often BI Software) but we feel technologies (especially coding) are dirty / low subjects and contractors can take care of it. You consider yourself lean because there are not too many people in the team if you do not count the contractors…

#3 : you clearly love technologies and data and you…

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