I have watched so many videos about the star schema concept, but this is the very first video I've seen to actually walk me through how to actually normalize a denormalized table of data. THANK YOU, Manuel. I feel like I finally get it now!
Agreed, this was a great video to share with my new Power BI expert-in-training. It's always been the one concept that I feel like is criminally underexplained, either ignoring it entirely, talking too high-level, or assuming you already know how to do it. And other guides use DAX which... is not what you're supposed to do when you're building the starting model. Useful to visualizing the idea, but not for practically doing it. This Power Query-based video is perfect.
Hey Manuel, thanks for making a mystery into something that I can use today! If only all tutorials were this straight forward to understand. Nice work!
Such a great video and instructor. I've always struggled with modeling with star schemas but this makes so much sense and I'm sure I'll come back for when I need a reference. Thank you!
Fantastic video. Thanks! I understand modelling, but am new to PowerBi and have been pulling my hair out on how to normalise data. This was everything I needed. ❤
Great video, however this aligns more with a traditional multidimensional model (snowflake). PowerBi is optimized to work with a tabular model which is more denormalized in nature. I think our response to introduce snowflake stems more from our bias towards DB design than dimensional modeling. Both will work though and you provided a great lecture
Man that was a very good video, very visual and nicely explained not too much info so I could relate and think about my own problematics and how it ties at the same time.. you have a new subscriber!!
I wish Power BI could integrate with a GraphQL spec or something like it. Where the query is the model and no need to manage relationships. However love your video and thank you!
Love your videos, informative and entertaining. Question though: if a new category were added to the data, wouldn't that potentially break the indexing that appears to be tied to the ascending sort step? And potentially shift all the index keys and royally mess up the data model? I guess I am unsure how the incremental index step works.
In my view the most important argument for modelling (quoting Ferrari/Russo): 'if you fix the model, the formula becomes easy to author and understand'
Thanks for sharing the video. I was able to create a star schema with my data by following along. Do you have a video where you show how to use the star schema tables and create visuals with them? I am trying to recreate visuals I had made before star schema vs with star schema and my visuals are coming out very differently. Bar charts with data in x and y axis along with the legend. Thanks!
Thank you! Very helpful video when beginning my Power BI adventure and want to apply good Power BI data models. However, one thing keeps me awake at night - - but I hope there is no reason for that other than my lack of knowledge - - well, the thing is, now that I have done all the normalisation in Power BI, data is organised very different from my starting point - - so will Power BI still be able to recognize the original data set from Excel that I will continue to use as a datasource, and what if I did make changes in my Excel datasourse - how should I apply these changes in Power BI If I eg added an extra column in my Excel model???
Hey Manuel, thank you for making this video. One thing I would like to ask, if the star schema had been modelled in the database but the surrogate keys are not numeric as you would normally expect, can this be utilised directly in PowerBI or do we need to create unique IDs within PowerBI? Are there any performance issues using non-numeric surrogate keys?
Hello, for anyone who has worked on data modelling; Can we apply similar steps when the scheduled update is switched on and all of Dimension tables needs to be created in in Business Client Project scenario, or Should we inform data engineering team to create these tables in backend?
I have a big problem, my fact table has a weight of 24 megabytes and when I divide 2 dimension tables like city and position. I do the same procedure but now my fact table has a weight of 70 megabytes when it loads that happens due to the combination. When it is a small table it also happens but due to the small size it goes unnoticed, please help
Hi thanks for the video! Great summary! At 12:09 for Denormalized Tables it lists "Best for increasing the spee of data search and analysis" on the slide but I interepret from what you are saying, the opposite. Can you exlplain the statement on slide a bit more please? Thank you!
What if more data need to be added into fact tables after creating index column in dimension table, merging and cleaning the fact table, how can some one remember all of those index key for each combination?
I have watched so many videos about the star schema concept, but this is the very first video I've seen to actually walk me through how to actually normalize a denormalized table of data. THANK YOU, Manuel. I feel like I finally get it now!
Awesome, thank you!
Agreed, this was a great video to share with my new Power BI expert-in-training. It's always been the one concept that I feel like is criminally underexplained, either ignoring it entirely, talking too high-level, or assuming you already know how to do it. And other guides use DAX which... is not what you're supposed to do when you're building the starting model. Useful to visualizing the idea, but not for practically doing it. This Power Query-based video is perfect.
This is extremely helpful! Thank you so much for making such a good interpretation of how data schema works in PowerBI!
I was confused because the basic star schema tutorials weren't giving me what I want but this video just solved my problem. Thank you
Short, Clear, Precise.
You are awesome! Keep it up
You're really good at explaining! Thank you for being so awesome!
We appreciate that. Thanks for watching!
First time I've seen query merging. It's really efficient. Thanks!
OMG, this is the topic I am searching from 10 days. very well expalained
Hey Manuel, thanks for making a mystery into something that I can use today! If only all tutorials were this straight forward to understand. Nice work!
Thank you!
You are a lifesaver. This is essential for building DWH from scratch. Thank you.
Such a great video and instructor. I've always struggled with modeling with star schemas but this makes so much sense and I'm sure I'll come back for when I need a reference. Thank you!
this is I love. Actual example and not just slide show of pictures and theory.
You are a great teacher. Taking the complex and making it simple is a great trait to have.
Glad you enjoyed!
Fantastic video. Thanks! I understand modelling, but am new to PowerBi and have been pulling my hair out on how to normalise data. This was everything I needed. ❤
i love you , have you onlyfans?
One of the best PowerBi videos on RUclips. Thanks Sir.
This is amazing, was able to apply immediately and get a better more efficient product. Thanks!
Glad it was helpful!
Thanks so much for making this topic easy to understand.
Glad it was helpful!
Fantastic job teaching this. Super helpful for me trying to figure out this tool.
Glad you enjoyed!
That's amazing video that getting me thru the basic of the data schema, short but very precise.
great video, well explained and straight to the point.
perfectly explained. Finally understood the concept
Great job! This was so easy to understand, appreciate the video!
Really nicely explained, this is going to help me clean up my messy models for sure.
Great to hear!
brilliant demonstration Thank you so much
Glad you enjoyed it!
Excellent information!! Thank you!!!
Glad you enjoyed :)
very clear and informative. thanks
Glad you found this helpful!
This is really good! Thank you very much!
one of the best one I seen so far
Very good explanation
if you want to understand what is star schema and how to use id in pbi, this video is for your you.
Excellent video! Thank you so much for this Manuel, just subscribed because of this video. Thanks a lot!
Glad it was helpful!
Great video, I've definitely learned something today. Thank you for this tutorial, I'll be looking to implement this going forward
Glad you enjoyed!
Absolutely excellent talk ... truly well delivered. I love the passion
Much appreciated!
Awesome video, Manuel. Thank you very much for sharing your knowledge!
Glad you enjoyed!
Great video Manual. This information is going to help me tremendously! 😀
Glad it was helpful!
Thank you very much sir!!!
Most welcome!
this video is a masterpiece!! thank you very much 🤓
Manuel, this was so useful. Thank you! I like how you present.
Great video, however this aligns more with a traditional multidimensional model (snowflake). PowerBi is optimized to work with a tabular model which is more denormalized in nature. I think our response to introduce snowflake stems more from our bias towards DB design than dimensional modeling. Both will work though and you provided a great lecture
Great video
Thank you! Glad you liked it.
Man that was a very good video, very visual and nicely explained not too much info so I could relate and think about my own problematics and how it ties at the same time.. you have a new subscriber!!
Glad to hear it!
Awesome!
Glad you enjoyed!
Great Video Manuel, and logic really well explained. :)
Glad you liked it!
Thanks!
You're welcome!
Thank you so much for this Dim in PowerBI
well explained thx
Glad you found it helpful :)
Very helpful! Thanks a lot.
Glad it was helpful!
Amazing job Manuel, really appreciate it
Amazing explanation! Thank you!
Excellent presentation, thank you
Powerful explanation.💯
Thanks for watching!
I wish Power BI could integrate with a GraphQL spec or something like it. Where the query is the model and no need to manage relationships. However love your video and thank you!
Simple effective, thank you so much.
Awesome Work Sir !! Thank you for the value provided . Subscribed !! ☺️
Thank you!
This guy is amazing.
We think so!
Really helpful awesome! Thank you very much.
You're very welcome!
Excelent
Glad you enjoyed :)
no comment only appreciated 100% for great JOB
Great! Thanks.
Great tutotial, very instructive.
Glad it was helpful!
Liked and subscribed. Excellent tutorial.
Thank You
You're welcome!
Love your videos, informative and entertaining. Question though: if a new category were added to the data, wouldn't that potentially break the indexing that appears to be tied to the ascending sort step? And potentially shift all the index keys and royally mess up the data model? I guess I am unsure how the incremental index step works.
Excellent video!
Glad you enjoyed!
Learned so much
AMAZING tutorial
superb
Thank you so much this is helpful
You're so welcome!
Amazing video
Thank you so much
Thank you so much!, truly helpful!
perfect!!
Thanks a lot
Keep going Please
We will!
I love Manuel!
Good job, great explanation.
Perfect!! Thanks
Glad it helped!
DIM tables. MOST Important part of data in model.
Good explanation.
Glad it was helpful!
Excellent - thanks!
perfect. thanks
Great video, thanks!
Glad you liked it!
Good stuff, bro! 🤌🏽
Appreciate it!!
Awesome 🎉 thanks
You’re welcome 😊
Thanks dear
Is there an excel file corresponding to the one used in the video that I can follow along with?
Awesome! Great job explaining the value of normalized data.
Glad you enjoyed it!
It's awesome
Thank you!!
Thank you!!!!
You're welcome!
@@PragmaticWorks I have a challenge of identifying the grain of a dataset, please where can I find your video on this?
Fantastic video. Thank you. Would be very interested in knowing what you were going to do with the Geo Dim.
That was great. Thank you.
Glad you enjoyed it!
Thank u❤
So easy on the ears
Glad to hear it!
In my view the most important argument for modelling (quoting Ferrari/Russo): 'if you fix the model, the formula becomes easy to author and understand'
Thanks for sharing the video. I was able to create a star schema with my data by following along. Do you have a video where you show how to use the star schema tables and create visuals with them? I am trying to recreate visuals I had made before star schema vs with star schema and my visuals are coming out very differently. Bar charts with data in x and y axis along with the legend. Thanks!
This was extremely helpful! Is this how I would tie in a date table, as well? Merge with the date table then delete the original columns? Thanks!
Thank you! Very helpful video when beginning my Power BI adventure and want to apply good Power BI data models. However, one thing keeps me awake at night - - but I hope there is no reason for that other than my lack of knowledge - - well, the thing is, now that I have done all the normalisation in Power BI, data is organised very different from my starting point - - so will Power BI still be able to recognize the original data set from Excel that I will continue to use as a datasource, and what if I did make changes in my Excel datasourse - how should I apply these changes in Power BI If I eg added an extra column in my Excel model???
Just to clarify: the redundancy in denormalized tables is not a problem in columnar storages (most of modern DWs)
Hey Manuel, thank you for making this video. One thing I would like to ask, if the star schema had been modelled in the database but the surrogate keys are not numeric as you would normally expect, can this be utilised directly in PowerBI or do we need to create unique IDs within PowerBI? Are there any performance issues using non-numeric surrogate keys?
Hello, for anyone who has worked on data modelling; Can we apply similar steps when the scheduled update is switched on and all of Dimension tables needs to be created in in Business Client Project scenario, or Should we inform data engineering team to create these tables in backend?
I have a big problem, my fact table has a weight of 24 megabytes and when I divide 2 dimension tables like city and position. I do the same procedure but now my fact table has a weight of 70 megabytes when it loads that happens due to the combination. When it is a small table it also happens but due to the small size it goes unnoticed, please help
Hi thanks for the video! Great summary! At 12:09 for Denormalized Tables it lists "Best for increasing the spee of data search and analysis" on the slide but I interepret from what you are saying, the opposite. Can you exlplain the statement on slide a bit more please? Thank you!
What if more data need to be added into fact tables after creating index column in dimension table, merging and cleaning the fact table, how can some one remember all of those index key for each combination?