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Sep 6Liked by Dylan Anderson

Interesting till now. Being a Quality professional in Data Analytics , looking forward for testing aspects and one general question is how one can define effort estimation for large projects.

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Both interesting questions! Check out the two part series on Data Quality to get you going (although it doesn't specifically answer those questions yet) - https://thedataecosystem.substack.com/p/issue-15-the-data-quality-conundrum

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Sure. Thank you

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May 12Liked by Dylan Anderson

I believe it is not just me, we all struggle with ROI when it comes to Data Management. Any thoughts or inputs would help. Thanks for this.

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Data management is a really tough one because it doesn't deliver immediate, direct value like ML or analytics. My article this week touches on Data Investment and an approach to viewing ROI. For Data Management specifically, I've tended to link it to all the other ongoing activities in the organisation and show how crucial it is to have underneath.

For example, if we are investing $500k in Data Science team, strong Data Mgmt. and high quality data will be a prerequisite for that team to deliver (so invest in mgmt. if you want that ROI to be strong). It is about showing the linkages between the domains rather than proving them out independently of one another

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