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would be awesome to see example of conceptual data modelling. There are tons of materials about logical and physical, but not about the conceptual. At the interviews people really like to ask how you are going to gather business requirements. Would be even better if you can record an interview-cracking video. I couldn't find anything decent on youtube for conceptual modelling.
Absolutely love your videos!!! Thanks for paving the way for millions of people to get their hands into data engineering and land a job. If I land any data engineering job, you definitely provided a major chunk of guidance !!
Yessss very excited about your next video on data modelling. Seeing actual examples will be incredibly useful, especially things like when to use one big table vs kimball etc.
thanks for solid intro. I found it very useful. I'd like to provide feedback in that studies have shown that all caps are more difficult to read so I'd recommend sentence case for your slides. Also, the yellow and black contrast on the slides is a little jarring but I love the content!
Benjamin, thank you for sharing these insights! This is an off-topic question but essential for me to - if I want to know more about data engineering/data modeling, what courses would you recommend? I am not a data person, these topics are becoming increasingly interesting to me, so I thought I could change my career
serve data in a useable way - thats pretty much how i've always explained what i like to do. Doubt i'll ever manage to get into a data modeler role though
I know that data engineers have to learn python but how much python is utilized for data engineering? What I'm saying is, do I need to know python inside out or should i direct it as specific aspects used for data engineering
Imo, not all entities require to be extracted out as a table. Sometimes the business value is not there, even though the business folks might talk about it. The perfect model doesn't exist, that is why migration exists when changes happen. It is the products or the production process that generate the data, checking how the product and process work will reveal more than what the business folks might talk about. Just my 2 cents.
Are custom fields the equivalent of feature engineering in Data Analysis? Are they decided on the business side through requirements, or does the DE make the best guess and present their model to the business stakeholders, who then accept or reject them?
Thanks for the nice information, if you could decrease your talking speed around 10% then it'll help more to non-native english speaking guys like me :)
Hi ! I’m a junior analytics engineer, and I’m building my first data warehouse. What’s your opinion about the books from Kimball “The data warehouse toolkit, 3rd edition” ? Is it good to understand the therocial part data modeling, or is it obsolete ? Thanks
