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!
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.
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. ❤
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!
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
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!
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'
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!!
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.
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?
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???
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!
Scenario Question: I'm pulling in data from a ITSM solution in which they use a 20 character alpha-numeric key for each validated attribute across all their tables. In most cases the Key has more characters than the text attribute. After watching this video, is it safe to say that I should just create my own keys, even though the fact and dim tables exist?
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?
Thanks for explaining! have a question, if a new category segment is added in the productdim table at the database level then how that will be reflected in the categorydim table which is created in power bi ?
In this video, dimensions are created dynamically in each refresh based on the original sales table of sales. So, if the new category shows up in any sale, the new category will be picked up by the query that creates the dimension of categories.
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!
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!
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.
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
OMG, this is the topic I am searching from 10 days. very well expalained
This is extremely helpful! Thank you so much for making such a good interpretation of how data schema works in PowerBI!
this is I love. Actual example and not just slide show of pictures and theory.
You're really good at explaining! Thank you for being so awesome!
We appreciate that. Thanks for watching!
Great job! This was so easy to understand, appreciate the video!
First time I've seen query merging. It's really efficient. Thanks!
You are a lifesaver. This is essential for building DWH from scratch. 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. ❤
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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!
One of the best PowerBi videos on RUclips. Thanks Sir.
You are a great teacher. Taking the complex and making it simple is a great trait to have.
Glad you enjoyed!
if you want to understand what is star schema and how to use id in pbi, this video is for your you.
perfectly explained. Finally understood the concept
Thanks so much for making this topic easy to understand.
Glad it was helpful!
This is amazing, was able to apply immediately and get a better more efficient product. Thanks!
Glad it was helpful!
Fantastic job teaching this. Super helpful for me trying to figure out this tool.
Glad you enjoyed!
Excellent information!! Thank you!!!
Glad you enjoyed :)
one of the best one I seen so far
great video, well explained and straight to the point.
Great video
Very good explanation
brilliant demonstration Thank you so much
Glad you enjoyed it!
very clear and informative. thanks
Glad you found this helpful!
This is really good! Thank you very much!
Really nicely explained, this is going to help me clean up my messy models for sure.
Great to hear!
That's amazing video that getting me thru the basic of the data schema, short but very precise.
This guy is amazing.
We think so!
DIM tables. MOST Important part of data in model.
Great video Manual. This information is going to help me tremendously! 😀
Glad it was helpful!
Thank you so much for this Dim in PowerBI
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
Powerful explanation.💯
Thanks for watching!
Awesome!
Glad you enjoyed!
Awesome video, Manuel. Thank you very much for sharing your knowledge!
Glad you enjoyed!
Thanks!
You're welcome!
Excellent video! Thank you so much for this Manuel, just subscribed because of this video. Thanks a lot!
Glad it was helpful!
Thank you very much sir!!!
Most welcome!
Very helpful! Thanks a lot.
Glad it was helpful!
Absolutely excellent talk ... truly well delivered. I love the passion
Much appreciated!
Great Video Manuel, and logic really well explained. :)
Glad you liked it!
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!
Thank You
You're welcome!
well explained thx
Glad you found it helpful :)
no comment only appreciated 100% for great JOB
this video is a masterpiece!! thank you very much 🤓
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!
Awesome 🎉 thanks
You’re welcome 😊
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'
Amazing job Manuel, really appreciate it
Manuel, this was so useful. Thank you! I like how you present.
Great video, thanks!
Glad you liked it!
Excellent video!
Glad you enjoyed!
Amazing explanation! Thank you!
Simple effective, thank you so much.
Thank you so much
Excellent presentation, thank you
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!
Great! Thanks.
Amazing video
superb
I love Manuel!
Perfect!! Thanks
Glad it helped!
Great tutotial, very instructive.
Glad it was helpful!
Awesome Work Sir !! Thank you for the value provided . Subscribed !! ☺️
Thank you!
perfect. thanks
AMAZING tutorial
Good stuff, bro! 🤌🏽
Appreciate it!!
Thanks dear
Good explanation.
Glad it was helpful!
Excellent - thanks!
Perfect! Thanks!
Good job, great explanation.
Thank you so much this is helpful
You're so welcome!
It's awesome
Thank you!!
Thank you so much!, truly helpful!
perfect!!
Thanks a lot
Keep going Please
We will!
Learned so much
Awesome! Great job explaining the value of normalized data.
Glad you enjoyed it!
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.
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?
Thank u❤
Excelent
Glad you enjoyed :)
That was great. Thank you.
Glad you enjoyed it!
Just to clarify: the redundancy in denormalized tables is not a problem in columnar storages (most of modern DWs)
Fantastic video. Thank you. Would be very interested in knowing what you were going to do with the Geo Dim.
So easy on the ears
Glad to hear it!
Is there an excel file corresponding to the one used in the video that I can follow along with?
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?
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???
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!
Scenario Question: I'm pulling in data from a ITSM solution in which they use a 20 character alpha-numeric key for each validated attribute across all their tables. In most cases the Key has more characters than the text attribute. After watching this video, is it safe to say that I should just create my own keys, even though the fact and dim tables exist?
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!
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?
Thanks for explaining! have a question, if a new category segment is added in the productdim table at the database level then how that will be reflected in the categorydim table which is created in power bi ?
In this video, dimensions are created dynamically in each refresh based on the original sales table of sales.
So, if the new category shows up in any sale, the new category will be picked up by the query that creates the dimension of categories.
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!