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I was thinking about making a course for finance people trying to get into programming and automating some of their BI and I stumbled upon this book. Really cool project btw :)
I was thinking that finance people would appreciate to have more resources on different ways to bring data in, export data to other tools and automate workflows. For instance, I see more and more people that use Google Workspace automate spreadsheets and presentations using Google's AppScript (unfortunately Javascript). Another example would be importing data from various databases, analytics or BI tools, creating whole data pipelines etc.
The underlying problem that I see is that many people try to get into programming, learn Python (for instance), but fail to understand how tools work together and how to create (reliable) data pipelines and ultimately abandon their aspirations.
That being said, I have several questions:
Do you think that's the case?
If so, do you know what tool and use cases these economics people would be most interested in?
If there's a need for such chapters, I'd be happy to contribute to them or even lead the way into writing them.
The text was updated successfully, but these errors were encountered:
nsobadzhiev
changed the title
More chapters for data sources (e.g Google Docs, automations etc)
More chapters on data sources (e.g Google Docs, automations etc)
Aug 20, 2024
I was thinking about making a course for finance people trying to get into programming and automating some of their BI and I stumbled upon this book. Really cool project btw :)
I was thinking that finance people would appreciate to have more resources on different ways to bring data in, export data to other tools and automate workflows. For instance, I see more and more people that use Google Workspace automate spreadsheets and presentations using Google's AppScript (unfortunately Javascript). Another example would be importing data from various databases, analytics or BI tools, creating whole data pipelines etc.
The underlying problem that I see is that many people try to get into programming, learn Python (for instance), but fail to understand how tools work together and how to create (reliable) data pipelines and ultimately abandon their aspirations.
That being said, I have several questions:
If there's a need for such chapters, I'd be happy to contribute to them or even lead the way into writing them.
The text was updated successfully, but these errors were encountered: