Types of Data Stores - OLTP, ODS, OLAP, Data Mart, Cube, etc

We will learn about various data stores that an organization has - OLTP, ODS, OLAP, NDS, DDS, Data Mart, OLAP, MDB or Cube.
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[@drdeepee2503]

You have very high quality content on this subject. Not sure why these videos didn't get as many views. Hopefully that would change soon.

[@SoftwareArchitectureAcademy]

Thanks for those words, this kind of motivation keeps me going!

[@rawoofmohammed6377]

Your videos are short,crisp and to the point. Thank you!

[@SoftwareArchitectureAcademy]

Glad you like them!

[@udayradhe6537]

so well explained, you should explain all datawarehouse concepts and data stores in one video

[@SoftwareArchitectureAcademy]

Glad you liked it - i have explained datawarehouse concepts here, to some extent - th-cam.com/video/vv0ReKrEQf4/w-d-xo.html

[@venkatr825]

can you elaborate where exactly the OLTP data is stored i mean in which databases if possible any example

[@SoftwareArchitectureAcademy]

Hi Venkat, Typically, OLTP is used to store live transactional data from customer interactions - one good example can be love payments data. OLTP system can be stored in any suitable database, there are no restrictions.

[@ChandraSekharAruru]

good learning info and also prestation. I want to update my self to data architecture do you have any online training sessions / courses please let me know

[@ashokrajann9351]

Hello sir
Greetings
One doubt
Generally dimension tables will contain unique values and less number of records compare to fact table or vice-versa of fact table
I'm quite confused to see denormalized data will be present in dimensional tables
Since denormalized means redundant data will be there
Kindly correct me if my understanding is wrong

[@SoftwareArchitectureAcademy]

Hi Ashokranjan, thanks for asking the question.
Dimension table can will have unique values that are similar to any lookup or reference table and hence less number of records.
The de-normalization and data redundancy will actually be present in a combination of fact and dimension tables to enable quick queries in-order to avoid costly joins. So a single fact or a single dim will always have unique records, identifiable with a unique key.

[@brookeguthrie3417]

Outstanding! Thank You very much.

[@SoftwareArchitectureAcademy]

My pleasure!

[@JP-vo1gi]

Any training courses ? Thank you !!

[@SoftwareArchitectureAcademy]

Hi JP, not at the moment. Will keep you posted, thanks!

[@bilo1897]

Great content thank you for your videos!

[@SoftwareArchitectureAcademy]

Thanks for your feedback!

[@ashanair5909]

Loving your videos

[@ahmetalperenyildirim6184]

thank you for sharing

[@SoftwareArchitectureAcademy]

Glad you liked it!

[@GIGONik]

Good

[@vjayvji0516]

simply good

[@SoftwareArchitectureAcademy]

Thanks Vjay!

[@harshitbajaj7549]

content is good but your way of explanation is boring to watch it continue till end. It is like anwering the questions in an interview. Learning can be fun if you taught in hindi with some desi examples.

[@SoftwareArchitectureAcademy]

Thanks Harshit for your feedback!