Types of Fact Tables in Data Warehouse | Transaction, Periodic and Accumulating

Подписаться 13 тыс.

Просмотров 87 тыс.

50% 1

Welcome to aroundbi.
In this tutorial, We will understand different types of fact tables - transaction fact, Periodic snapshot fact and Accumulating snapshot fact table - based on individual requirements, we create and use these different fact tables in warehouse schema. We will go through a comparative study to evaluate which fact table type is better in what scenario.

Опубликовано:

2 окт 2024

Ссылка:

Скачать:

Готовим ссылку...

Добавить в:

Мой плейлист

Посмотреть позже

Комментарии : 57

@yahooviareifsd 6 лет назад

Very Nice ... Shot n crisp info... Have one question if there is a periodic snapshot fact table or accumulating snapshot fact table then there should be be a transactional fact table by default, ... Right?

@aroundBI 6 лет назад

In my experience, I have seen a transaction table also along with periodic snapshot. Not a rule but common practice.

@kumarprabhu 10 месяцев назад

Can a periodic snapshot contains lowest level of granularity...In other words business wants to take a snapshot of the entire fact table on daily basis, so that on a particular day they want see all the relevant detail rows anytime possible..How to handle this.

@kiranthemanable 3 года назад

Thanks for the video

@shashikanthpai2034 6 лет назад

another good video

@rickmemmer5625 6 лет назад

Another hallmark of excellence! I continue to be amazed by the quality of these videos -- it would be hard to improve on them. Thank you very much for your phenomenal work!!

@aroundBI 6 лет назад

Your feedback is big encouragement to continue our effort. Thanks a lot.

@rickmemmer5625 6 лет назад

You're very welcome! Thank you for the kind reply! :o)

@mloera81 3 года назад

Great video and playlist, thanks! Just an observation but when you are discussing Update frequency isn't it: Transaction - None Periodic - at defined intervals Accumulating - at each milestone

@SandhyaSingh-zf6qr 4 года назад

Nice 👌.. I have a question- what is additive, semi additive and non additive?

@midorile 5 лет назад

This video is amazing, I was reading the data warehouse toolkit and I love it, but this part was so confusing IMO. So I browsed around and found this, nothing left to clarify!

@davida6146 4 года назад

Same!

@ih4722 4 года назад

@@davida6146 Same!

@CaribouDataScience Год назад

Thanks, that explained a lot.

@suleimanbashirshamsudeen3785 2 года назад

Really good video series on datawarehousing concept..what type of fact table will you recommend for a CRM Saas application

@shreyalande16 4 года назад

Awsome !!!

@nilabjachattopadhyay8863 6 лет назад

why is the accumulating fact table not considered as a dimension table? it has the date dimensions.. same as role playing dimensions

@komaljaiswal2826 6 лет назад

Good explanation! Thanks!

@sukumar44 3 года назад

2 suggestions: 1) please order your videos in the correct way within the playlist 2) please go slow while explaining I have watched all your videos and liked the content.

@manualchnn 6 лет назад

Thank you great one

@DataEngineeringGeek 2 года назад

If a Transaction has more than 1 product that have been bought/sold then in Transaction Fact Table Transaction number will be the Degenerate Dimension and same transaction number will appear twice as two different product FK are there, with different price and quantity for each product in Transaction Fact table. So, it has one row /transaction does not necessarily hold true.

@SumaK-j2q Год назад

it will be great if u also add an addition where,, u can show how to add a surrogate key from customer/ product dimension as well.

@Roamingcurlcircuit 3 года назад

is unit price a additive fact or non-additive?

@forstreetanimals3882 2 года назад

Why you are not uploading video more than one year in you channel..?

@rajeshmacpant 6 лет назад

Very well Explained, thank you

@tryambakeshwarkatre4666 3 года назад

thanks for this meaning full explanation...........................................................................

@lumaswwar995 3 года назад

you are speechless, Very very good Explained, thank you

@Bharath_PBI 3 года назад

How can a periodic snapshot fact table be less in size when compared to transaction fact? I have worked with snapshot facts which are in hundreds of millions whereas transactional fact are just in tens of millions.. can't say that is always less, as it depends on the grain

@ranganathanb2586 3 года назад

True

@maryam4071 6 лет назад

Thank you for the video, I need a help, User tracking, such as Google analytics data, we need to keep track of the user, what type of fact table is?

@aroundBI 6 лет назад

Great question. Fact table type will be dependent on two factors- first is volume of data that we can expect. Most common criteria or key to store data would be unique visitor or visitor # or ID. Second factor would be type of analytics we want to do. Option would be periodic snapshot but I would go ahead and gather every detail just as transaction table. Again, thanks for your wonderful question.

@maryam4071 6 лет назад

Thx @aroundBI for your response, I didn't get your sentences here "Most common criteria or key to store data would be a unique visitor or visitor # or ID". As far as I understood the lowest level of granularity in case of the snapshot is the "date", in my case is 'sec'. so we will get a row per each visitor Id + time. this would be unique over the file. Then this looks like a snapshot, right? Are u confirming me? Mostly you are selecting snapshot policy just for avoiding of data grow in fact, right?

@NripaEmpowerthroughknowledge 2 года назад

@@maryam4071 🙏

@malakwaseem1166 3 года назад

What is historical data in data warehousing?

@akashverma5054 4 года назад

Hi need some help related dimensional modelling its urgent

@jojappakoyyuru8301 4 года назад

very much useful sir. Thanks a lot.

@chinmayee_traveller 3 года назад

very well Explained!! :)

@travel_the_world252 6 лет назад

Thank you ! Well explained!

@MrIrrepressible 5 лет назад

thanks you again for these videos, u are helping many people.

@MrMadmaggot 11 месяцев назад

Nice video man, thx a lot.

@bidata4790 2 года назад

Excellent Thank you.

@harishgovekar3274 4 года назад

Best Information, thank you Team.

@nishanthkumar4743 4 года назад

I really liked the way you explained the tables with real time examples.. I was looking for multiple videos to get the correct understanding but this has enough information... Thanks much