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John Wessel's avatar

So let me be more specific. The way I’m seeing Data Factory being used (a component of Fabric) is taking SSIS packages and now running them in the cloud. That’s not the only way to use data factory - but as long as you don’t have to rewrite SSIS jobs I imagine many people won’t... but then you have the limitations of the tech that was already in place - with some benefit of now having a cloud runner. PowerBI is also part of fabric - and the reason I hear from others as to why they use it is ALWAYS “because it was cheaper” not better. Plus the cheaper was just in LICENSING cost (not counting other costs).

The bizarre part - Microsoft Excel is a tool people still truly love. I’m sure MS product teams would love to bottle that Excel lovin’ and spread to other MS data products - but IMO that hasn’t happened.

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RowanC's avatar

I read this and worry that my concerns are real that the data world has been hijacked by people who would rather create governance frameworks and controls, than find (or allow others to find) insights and understanding in data. I think this is in large due to its promotion to ‘the new oil’ and the explosion in roles which are often siloed in the data stack. The increase in status leads to greater scrutiny, and the increase in silos increases the likelihood of errors and mistakes due to lack of insight…which leads again to greater scrutiny.

In governance specifically, I think there is a data lifecycle which starts being produced by business process, when that process is entered into an application, and via ingestions and transformations into reporting, through influencing and into action/decisions. So far regulatory governance approaches I’ve seen only inspect the problem of (a small amount of the ingestion,) transformations and models, but still manages to miss the two key ends of the process. I believe this is one reason why it’s boring - it seems like overhead that is added doesn’t solve the key issue of knowledge gaps in understanding what processes, developer choices, and manager idiosyncrasies help data be productive and valuable

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