Dimensional Modeling

[@chadrob]

I've seen hours of videos on data warehousing. These are the most valuable 56 minutes.

[@MightyMike55]

Well said

[@vaibhav8382]

53 minutes*

[@sndselecta]

100% agreed

[@maryjones2175]

Could not agree more, this is the best video on data warehousing I have watched so far!!

[@P_Belle]

Agreed! Conversational tone, appropriate visuals, and well-paced. I'm in a $4k EDW graduate school class that teaches from bulleted PowerPoint slides. Doesn't compare 🙆😟

[@avenuech39]

The most understandable, detailed & overall introduction to Dimensional Modeling, with clear key words explanation and logically sequential arrangement on the slide content. Thanks Bryan!

[@prithvikumar3751]

This is the most informative session I have ever seen! 54 minutes of pure knowledge. If only everything I had an interest in learning was taught by Bryan!

[@BryanCafferky]

Thanks. What are your tech learning interests?

[@bradjohnson9022]

This is by far the best guide to dimensional modeling I've found on the internet!

[@markparee99]

Using for an interview prep. Great refresher. Perfect length and depth of content...

[@kasiatuszynska486]

Perfect combination of experience and theoretical handle on the subject. Thank you for the time it took to record it.

[@BryanCafferky]

You're welcome. Glad it was helpful.

[@johnlamarre7330]

I come from an OLTP software data architect side of the house and only had to hand off streaming/replication to an ODS. I just took a role that will require dimensional modeling. So glad I found your video. This clicks.

[@BryanCafferky]

Glad it is helpful.

[@terryxu1481]

Hi Bryan, many thanks to provide this tutorial. The most solid foundation tutorial on data warehouse & dimensional modelling I have even seen. For those who want to build their career path as a data analyst, data architect etc. This is the best start point. I really regret that I did not see this video 2 years ago when I start off my career.

[@BryanCafferky]

You're very welcome!

[@jilanimohammed4656]

These are the best 53 minutes I've spent recently. Crisp and Clear. I feel much more confident and I request more videos on Dimensional Modeling. Thank you for your effort.

[@BryanCafferky]

Thanks. I did do a video on Slowly Changing Dimensions which is a big area for interview questions. What topics are you most interested in regarding dimensional modeling?

[@manarlab84]

I'm grateful for the time and efforts you put in explaining one of the key concepts anyone deals with enterrpise data needs. Clear and comprehensive. Thanks a lot

[@Molaa21]

Amazing video. Well explained. Uploaded 3 years ago, still valid for educational and professional training for 2020. Thanks Bryan!

[@kcmalik5992]

Good sir, I typically never like or comment KZbin videos. This was a must. You are masterful, and could quite possibly mint some people into data engineers off of this video. God bless you. I hope to become a teacher like you one day

[@BryanCafferky]

Thank You

[@paoloogr]

My current favorite channel on KZbin being a senior data engineer. I would like to have a video created by you telling more about what cubes are, OLAP, ROLAP, etc. This kind of nomenclature is getting more and more rare and people joining data engineering in this modern data stack area should understand them well so that they can understand how we got here and also talk to people familiar with this data engineering nomenclature.

[@BryanCafferky]

ROLAP and MOLAP are only used in the legacy SSAS Multidimensional Models. They were cool but the Tabular model does not use them b/c everything is in memory. Thanks for the suggestion. Are you using SSAS Multidimensional Models?

[@Lego-tech]

Many Thanks !! This is the best video I have even seen on this subject. Simple explanation of all complicated areas.

[@TheMadMagician87]

I'm about 4 or 5 years late to this party. You've still done a great job in this video compared to many other sources. Thanks, and well done!

[@BryanCafferky]

YW and thanks for watching.

[@pranshumishra]

This is premium content on the topic. Simple yet effective explanation shows your understanding of the subject. Thank you Bryan!

[@BryanCafferky]

Glad it was helpful! Thanks

[@risebyliftingothers]

By far the MOST lucid and practical no-nonsense explanation of key terms. Loved it!

[@BryanCafferky]

Glad it is helpful! Thank you for the kind words.

[@paulm3106]

An excellent video on data warehousing, easily the best I've seen.

[@stuieblack]

Quality. Seeing your videos, I realise that this is the subsection of my role that I enjoy the most and need to learn more about. Great video.

[@nandk98]

A very comprehensive and fully understandable video during my very first viewing itself. I felt like having read a high quality book on the topic within an hour. Bryan never wastes time on unnecessary talks and very effectively concentrates on the core through and through. Thank you!!

[@BryanCafferky]

Thanks

[@nandk98]

@@BryanCafferky My statement was true. Not just a passing compliment. I got a full perspective on what is dimension modelling and how it is different from Data warehousing. Leave alone warehousing, it actually helped me in designing various reports using data from Database tables. I was able to see the common threads that run through them all.

[@anjaneynaik3080]

The concept has been explained thoroughly with real time examples. Thanks Bryan.

[@BryanCafferky]

YW. Thanks for watching.

[@Vermitude]

A very useful introduction to data warehousing and the common terminologies, presented in an interesting and easy to understand manner. IT was a very quick 53 minutes - I only meant to get an idea of the content and then watch it later - but got completely absorbed.

[@BryanCafferky]

Thanks. Glad you liked it.

[@sshfromhere]

Great presentation!👍 Thank you Bryan ! 👏

[@BryanCafferky]

YW. Glad it is helpful.

[@himanshityagi5055]

I wish I had watched it earlier when i was struggling to understand Datawarehousing and Dimension Modeling. Very informative video. Every second was worth spending.

[@BryanCafferky]

Thanks. Yeah. I struggled understanding this too for some time. Glad it helped.

[@wentingzhu343]

among several videos i watched on dimensional modeling, this is the one with more insight and experience sharing!

[@marcosoliveira8731]

Lovely way of teaching. Looking up for more of your material about data warehouse on the web.

[@stalsams179]

I dont usually spend time watching a 53 min learning video most of the time unless the course and the orator is really worth it. Trust me sir, you kept me glued every minute. God bless you Sir !

[@BryanCafferky]

Thank you!

[@stephenhordes4244]

Thanks Bryan, great video.

[@akshaybaura]

I have been working in data warehousing for the last 5 years and this video gave me the answer I have looking for so long- why is there so much normalisation in data warehouses we see today? Nobody ever gave me a satisfactory answer but you did sir. Big thanks !! This video deserves to be on the billboard.

[@BryanCafferky]

Great! Glad it helped!

[@manankashyap7726]

One of the best videos I’ve seen on DM!!

[@simondavidvgm]

AMAZING lecture, Bryan - thanks so much! Exactly what I was looking for and an extremely well articulated 56 minutes.

[@consumer323]

This was an excellent primer. I was alert and it really grounded me on a number of key points. Thank you so much for this contribution.

[@user-yw1ef7hx4v]

The best video I have ever watched till date. Very well explained and neatly presented. This video helped a lot!!!

[@BryanCafferky]

Glad it was helpful!

[@erb6411]

This is so helpful. I'm modeling a data warehouse for my Org and only have experience with OLTP. This has saved so much headache

[@BryanCafferky]

Great! Yeah. Dimensional Modeling is a very different mindset. Good luck!

[@terribradshaw4366]

Thank you for this excellent presentation on Dimensional Modeling. I'm a student and it was so easy to follow because you made it interesting and you provided some excellent examples to support your slides.

[@BryanCafferky]

Thanks. Glad it helped. Hope you find my other videos helpful too.

[@cannonkalra7133]

This is what I subscribe internet for, it's beautiful piece of 53 mins straight

[@BryanCafferky]

Thanks. Hope you check out my other videos like the ones on Databricks and Python too.

[@rishabhbhatt7373]

Great content Bryan. Great level of detail and insights (from actual experience). Please keep it up !

[@LEI8037]

I am listening you for the first time and I found out that you are a great teacher.

[@BryanCafferky]

Thanks!

[@LEI8037]

@@BryanCafferky After an year I am listening again to refresh concepts.

[@individualassignment2661]

this is great Dimensional Modeling tutorial ever.. !! Thank you so much, sir..

[@user-ob2ox5nk8v]

Crisp, Precise and understandable!

[@GokulShanth]

For someone just getting started, this was amazing thank you so much!

[@BryanCafferky]

YW!

[@hgiang100]

Thank you Bryan for this video. You did an excellent job of explaining the concepts data warehouse design.

[@BryanCafferky]

Thanks!

[@tregatregs8804]

This is a must watch video for anyone having a hard time understanding Dimensional Modeling. Wish you could do a full series on Database systems and Warehousing.

[@BryanCafferky]

Thanks. What specific topics are you thinking of?

[@houstonfirefox]

Very well presented! Clear and concise with real-world use cases!

[@billrosmus6734]

This is an excellent primer. The best one I've seen. I'll recommend it if anyone asks for advice on a good starting point. One point however: USER STORY. In 99% of Agile Software Development, the example from that book is NOT a User Story. A user story actually describes something that needs to be done and why. e.g. As a business manager I need to be able to drill down into the types of sales act my book stores to see the types of books being purchased, how they are being purchased, how they are being paid for, down to the level of the book title, so that I can understand what is being sold and better stock my stores. What the book you mention is actually doing is closer to a Use Case. There is semantic impedance going on. But it's just data. :) Anyway, I really do like this video and think the approach of using use cases is very good. I think though that there will be some need to translate between different groups kind of like what is a location to different systems. :)

[@BryanCafferky]

Thanks!

[@C_G_1962]

The ideal video for a dba trying to reach the dw world (using mssql server and also Azure) . Thanks a lot for the video !

[@BryanCafferky]

Glad it helped!

[@4rmtinc]

A nice and concise presentation of dimensional modeling for data warehouse.

[@2001july06]

Amazing simple and focused explanations. Thanks Bryan

[@BryanCafferky]

You're Welcome! Glad it was helpful.

[@shivamahirao5377]

You're a savior, thank you Bryan.

[@BryanCafferky]

YW. Glad it helps.

[@aaragon0902]

Thank you so much!! Struggling through my data modeling/structuring course and your video was incredibly helpful in understanding dimensional modeling.

[@BryanCafferky]

Wow! Really glad to hear that. Thanks for letting me know.

[@maniji5756]

Thank you, loved the content and how well it was structured and presented. Looking forward to your other tutorials!

[@mirdhapuneet]

Hi Bryan, This video is one of the best videos have watched and has every information required, to the point and well described...Hats off...Thank You. Highly recommend must watch for everyone who is working in DWH domain.

[@BryanCafferky]

Thanks! Appreciate the kind words.

[@vijayd15]

Best video on DW design ever!

[@mohdfaisal9564]

Hi Bryan, This video is one of the best videos have watched and you have covered every piece of information required to the point and well described...Hats off...Thank You. Highly recommend must watch for everyone who is working in the DWH domain.

[@BryanCafferky]

YW and thanks for watching.

[@ghazitozri4989]

Thank you sir, you saved my life.

[@ohnotoyota4692]

Excellent, specially focus on process model. Thank you

[@BryanCafferky]

YW!

[@tobman781]

Great presenation. Very clear and to the point!

[@vikaschoudhary6904]

Great tutorial sir , Thank you so much for such relevent information .

[@BryanCafferky]

You are most welcome

[@clintp3504]

Excellent video! Thanks for sharing

[@BryanCafferky]

YW

[@helovesdata8483]

I'm getting into data engineering and I really enjoyed this content.

[@dylankelly3318]

Great video Bryan.

[@astersathya]

Excellent Video and loved it. Being an OLTP modeler, this gave me a very nice idea about dimension modeling. The only one thing which I wanted to bring it to your attention that, When you talked about 7W's of dimensional modeling, it only had 6 Ws and I was searching for the 7th one :)

[@BryanCafferky]

Hi Sathya, Great observation! Actually, the 'How Many?' is one of the 7 but yeah, it is an H not a W. The book 'Agile Data Warehouse Design' presents it that way so I did to. It should be the 6 W's and 1 H of Data Warehouse Design but that is harder to say. :-) Actually, it helps me remember the How because it is different. Thanks!

[@msdew9885]

@@BryanCafferky hoW? What? When? Where? Who? hoW many? Why? makes 7. Thanks for the video. Very informative!!!👍

[@thehouse2620]

Thanks, This is very helpful. When you discussed the scenarios regarding a person getting married, it triggered a bunch of other questions I can ask for my project. I enjoyed the descriptions of what is fact vs what is dimension.

[@Ari-lu5ve]

Thank you so much for this! Very organized lecture, and I love how you included the time stamps.

[@mohammedansari818]

This is the first time I loved blue screen on my computer. :) Very good advice.

[@lyreco7910]

Absolutely amazing video, thanks Bryan!

[@BryanCafferky]

YW. Glad it was helpful.

[@aiikaiik]

Great Job Bryan, great content .Thanks for sharing

[@BryanCafferky]

Thanks!

[@YeetYeetYe]

Absolutely amazing explanations.

[@saurabhjain2005]

You are amazing!! Thank you so much for this. Best summary you can get and which can make you talk like a pro..

[@BryanCafferky]

Thanks.

[@joaorataoo]

Thank you so much for sharing your knowledge and your skills to teach them in a so clean, so comprehensible.

[@BryanCafferky]

Thanks. So glad it is helpful!

[@creativeluf]

Great explanation of dimensional modelling. Highly insightful.

[@richardogujawa-oldaccount1336]

Great lecture, definitely worth the watch!

[@sendilbm]

Amazing video, very detail level. Thanks so much.

[@SuperAerodragon]

@BryanCafferky Thank you for taking the time to put this together. This is a great foundational video for anyone getting started and presents the subject in a very relatable way.

[@BryanCafferky]

Thanks.

[@Martin-lf9se]

Very well done and explained. Thank you for sharing your knowledge.

[@BryanCafferky]

Thanks for watching.

[@sumit12345yadav]

@Bryan Cafferky - thank you for creating this great video. Its really a marvel , simple, realistic approach to understand.

[@torque6389]

Excellent job! Thank you for this wonderful video!

[@ragacbe]

It's a great content and presentation. Thank you very much for this wonderful work!

[@BryanCafferky]

YW!

[@nathankomer8699]

Priceless resource. Much appreciated!

[@barbararibeiromaia1502]

This video was perfect to answer my questions! Thank you!

[@BryanCafferky]

Glad to hear that!

[@pradeepnagaraj7347]

Excellent explanation Bryan!!

[@haiderali-uf4gy]

best video on data warehousing on youtube..

[@saisanikommu8551]

I listed out some topics (after my failed interview )to gain clearcut understanding and this video answered all my questions in detail,Sir big thumbs to you ,if possible please do a video on interview questions and how to answer them (Dw,DBMS concepts).

[@BryanCafferky]

Hi Sai, That's a great idea for a video. Do you have any specific questions in mind? BTW: Interviews always have questions to stump you. But I'd like to help with a video that helps. Thanks! Bryan.

[@mathinsovie9954]

Wow. well detail and explainable. Thanks Bryan

[@BryanCafferky]

YW!

[@michaelwoodman2746]

Thanks Bryan. This is a really useful overview; great to have the fruits of your extensive experience.

[@BryanCafferky]

Thanks Michael!

[@martinmkca2320]

Thank you very much for this GREAT presentation!!!!

[@hugomichaelnunezmejia3384]

THANK YOU FOR THE CLEAR EXPLANATION!!!

[@valentinussofa4135]

Amazing lecture. Thanks Sir. 🙏🙏🙏

[@jimpanging87]

Great video, great explanation!

[@stefangabor5985]

Great presentation.

[@BryanCafferky]

Thanks

[@druthorah]

Excellent explanation! Thank you for this.

[@myth00s]

Just to point out that "dimensional" is not the opposite of "relational". The latter just means you are using certain abstract data types (relations & tuples, i.e. tables & rows) to model your data at the logical level. Both dimension tables and fact tables are ... tables, i.e. relations, if implemented in a relational database. "Dimensional" means syntactically formulated around a specific sentence schema with empty spaces to be filled in about observations (facts) that have taken place in a certain context (dimensions).

[@BryanCafferky]

Right. Entity Relational (ER) Modeling is used to create optimized OLTP architectures whereas Dimensional Modeling is used to create optimized reporting data warehouse architectures. It is critical that DW designers do not apply ER to a DW or they will get performance and reporting issues. Coming from an OLTP background, that took me a bit to get.

[@excelrati]

Thank you so much for this video. I really appreciate your efforts to explain this in the best possible way 👍🏻

[@BryanCafferky]

Glad to help!

[@Seamonkey1981]

outstanding overview, well done

[@AaronJOlson]

Great video, thank you!

[@dalibormares4917]

very clear, thanks Bryan

[@nicoyou11]

Excellent education. Thank you!

[@BryanCafferky]

YW. Please share my channel with others on social media.

[@xloganp8925]

Thanks a ton Brian, that was very informative and easy to follow.

[@BryanCafferky]

Thanks. Glad it was useful.

[@Boatsman99]

Excellent and very informative video. Thank you very much.

[@FedericoLov]

excellent! This is really missing from the typical data science curriculum

[@BryanCafferky]

Yeah. It is often overlooked.