Datalake can contain unstructured, semistructured, and structured all kinds of data. purpose of datalake is to store raw data for various downstream teams. Whereas Data warehouse is for structured data only. It is a read-heavy system for analytical needs. ETL: is used where source data is not bulky and transformation logic is clear for a specific purpose, Only the transformed data needs to be loaded in the target system, enhanced security etc. ELT: is used where a huge volume of data is being processed, and multiple transformation logics will be applied to the raw data by multiple teams, in case of real-time analytics etc. Many to many relationships can be handled by introducing a bridge table between the tables. The bridge table will have 1:M relationship with the other tables.
not completely agree with the first difference you explained for ETL vs ELT, both can be used to load data warehouse or data lake, however, the decision on which one should be used is based upon the infrastructure requirement, in ELT you can leverage the power of your target data base for load as well as transformation but in case of ETL you must provision a third server/ compute machine only for the transformation purpose. Happy to read if you have any other view on it..!!
You are a good tutor and a request, why don't you post some tutorials on data modelling that would be helpful. Thank you for this video it is very helpful.
@DatingData by Pritha Hey, why you have stopped making these videos? you are really good at these technical videos and Videos are knowledgeable. I suggest you to continue to make such videos frequently. fyi, i searched to DM you , no where to find , so i am communicating to you here
Well a Googler and professional data modelling trainer at Please check my linked page for my experiences. It will be really good if you post your questions and ask what exactly you are looking for.
I don’t feel that explanation was not clear TBH. But ma’am don’t you think that these questions are very simple? Is this truly the level of interviews?
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Datalake can contain unstructured, semistructured, and structured all kinds of data.
purpose of datalake is to store raw data for various downstream teams.
Whereas Data warehouse is for structured data only. It is a read-heavy system for analytical needs.
ETL: is used where source data is not bulky and transformation logic is clear for a specific purpose, Only the transformed data needs to be loaded in the target system, enhanced security etc.
ELT: is used where a huge volume of data is being processed, and multiple transformation logics will be applied to the raw data by multiple teams, in case of real-time analytics etc.
Many to many relationships can be handled by introducing a bridge table between the tables. The bridge table will have 1:M relationship with the other tables.
not completely agree with the first difference you explained for ETL vs ELT, both can be used to load data warehouse or data lake, however, the decision on which one should be used is based upon the infrastructure requirement, in ELT you can leverage the power of your target data base for load as well as transformation but in case of ETL you must provision a third server/ compute machine only for the transformation purpose.
Happy to read if you have any other view on it..!!
I agree with you.
correct
Great example and shared insights! Very helpful!
Please put more videos like this, it is very helpful for student like us.
Thanks :)
Your explanation was so easy to understand like a friend explaining before exam!!!! Please make more videos.. Thank youuuuuu!!
You are a good tutor and a request, why don't you post some tutorials on data modelling that would be helpful. Thank you for this video it is very helpful.
bane extralu ,,,,,,,
I can see explanations of 2 questions( i.e., Data Warehouse vs Data Lake and ELT VS ETL) , what is the 3rd data modeling question ?
Can you please tell about the reverse engineering for XML or Oracle DB?
Could you please explain in detail, how to resolve many to many relationships? (I didn't get in this vodeo)
We solve many to many relationships by creating a bridge/ linked table which act as intermediate table between other tables.
Sure. Will explain in my next tutorial.
Could you please explain the differences between different data models(Inmon,Kimball,3NF,Dimension Modelling,Data Vault).
Sure. In my next tutorial.
kaunsi book padni chaiye data modelling par ??
very nice
Nice explanation
@DatingData by Pritha Hey, why you have stopped making these videos? you are really good at these technical videos and Videos are knowledgeable.
I suggest you to continue to make such videos frequently.
fyi, i searched to DM you , no where to find , so i am communicating to you here
very good explanation
I love your gestures
Good one ❤
what is your linkedin profile?
Can you please post more videos on data modeling. Thanks
very helpful, thanks a lot
Awesome video পৃথা দি, প্লীজ ডেটা মডেল এর আরো use case video বানান
Really helpful!
Nicely explained. Thank you. Please keep it up!
How to connect with you?
Mail me at tina.pritha@gmail.com. I will share my number over mail.
Haeyy
"basically" became Data Redundant .... try to use less.....
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no clear explanation. She might be fresher.
Well a Googler and professional data modelling trainer at Please check my linked page for my experiences. It will be really good if you post your questions and ask what exactly you are looking for.
I don’t feel that explanation was not clear TBH. But ma’am don’t you think that these questions are very simple? Is this truly the level of interviews?