11 Microsoft Fabric Data Pipeline: How to do Incremental Load Using Copy Activity in data pipeline

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11 Microsoft Fabric Data Pipeline: How to do Incremental Load Using Copy Activity in data pipeline

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Күн бұрын

Microsoft Fabric Tutorial Series- How to do Incremental Load Using Copy Activity in Microsoft Fabric data pipeline.
Microsoft fabric data pipeline script activity: • 03 Microsoft Fabric Da...
Microsoft Fabric data Lakehouse end to end project - • 003 Microsoft Fabric L...
If you want to know more about Microsoft Fabric data Warehouse, Please watch below videos-
1. Create Microsoft Fabric Data warehouse: • 001 Microsoft Fabric D...
2. load data into Microsoft Fabric data warehouse using Data Pipeline: • 02 Microsoft Fabric Da...
3. Create table in Microsoft Fabric data warehouse: • 003 Microsoft Fabric D...
4. load data into Microsoft Fabric data warehouse using Copy into Command: • 003 Microsoft Fabric D...
5. Transform and load data into Microsoft Fabric data warehouse using T-SQL Procedure - • 004 Microsoft Fabric D...
keywords:
Microsoft Fabric data pipeline
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------------------------------Microsoft Fabric Overview------------------------------------------
Microsoft Fabric is an end-to-end analytics solution with full-service capabilities including data movement, data lakes, data engineering, data integration, data science, real-time analytics, and business intelligence-all backed by a shared platform providing robust data security, governance, and compliance. The platform is built on a foundation of Software as a Service (SaaS), which takes simplicity and integration to a whole new level.
With Fabric, you don't need to piece together different services from multiple vendors. Instead, you can enjoy a highly integrated, end-to-end, and easy-to-use product that is designed to simplify your analytics needs.
Microsoft Fabric brings together new and existing components from Power BI, Azure Synapse, and Azure Data Explorer into a single integrated environment. These components are then presented in various customized user experiences.
With this new tool Data Engineers can visually integrate data from multiple sources, data scientists can model and transform data, data analysts can bring together multiple datasets and enable deeper insights, data stewards can govern data all from one place, business users can work directly with data uncovering and shaping the intelligence they need to make critical decisions that drive growth.
Fabric brings together experiences such as Data Engineering, Data Factory, Data Science, Data Warehouse, Real-Time Analytics, and Power BI onto a shared SaaS foundation. This integration provides the following advantages:
* An extensive range of deeply integrated analytics in the industry.
* Shared experiences across experiences that are familiar and easy to learn.
* Developers can easily access and reuse all assets.
* A unified data lake that allows you to retain the data where it is while using your preferred analytics tools.
* Centralized administration and governance across all experiences.
With the Microsoft Fabric SaaS experience, all the data and the services are seamlessly integrated. IT teams can centrally configure core enterprise capabilities and permissions are automatically applied across all the underlying services. Additionally, data sensitivity labels are inherited automatically across the items in the suite.
Fabric allows creators to concentrate on producing their best work, freeing them from the need to integrate, manage, or understand the underlying infrastructure that supports the experience.
Topics Covered :-
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Keyword :-
Microsoft Fabric
Microsoft Fabric Lakehouse
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Fabric Data analytics
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Onelake
Data Engineering
Data Science
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Пікірлер: 17

@praveenkakumanu919 6 ай бұрын

Really You are super Bro. you explanation is packed and intuitive

@DataVerse_Academy 6 ай бұрын

Thank you so much 🙂

@praveenkakumanu919 6 ай бұрын

very practical explanation. Thanks

@moeeljawad5361 17 күн бұрын

Thanks for your video, very intuitive and impressive. I have a question, if your Table_List table is saved as a delta table from a python script, and i would like to have the Max_value updated.... I believe i will not be able to keep the stored procedure, right? if not should i be replacing it with a notebook activity? Thanks

@DataVerse_Academy 16 күн бұрын

Yes you are right you will not be able to use stored procedure to update a delta table. You need to create a notebook for that.

@rossgh76 7 ай бұрын

thank you for creating this great video🙂 Could you do this using Dataflow Gen2 in Fabric?

@DataVerse_Academy 7 ай бұрын

2 Microsoft Fabric DataflowGen2: Incremental load from Azure SQL DB to Warehouse using DataflowGen2 kzfaq.info/get/bejne/h6iIjZyYxJymiXk.html You can check this. Let me know if you have any specific requirement.

@balajikrishnamoorthy7352 8 күн бұрын

will this work if we delete or update a data in the source table ?

@DataVerse_Academy 7 күн бұрын

It will work in case of update , not in delete. As it’s incremental approach not CDC.

@pankajmandania1785 5 ай бұрын

Thank you for tutorial. One comment. I am fetching my data from Lakehouse and lakehouse allows me to get only a table so if i have to filter the incremental column and incremental value, i cant do that with lakehouse. so how would you approach the problem? i am trying to use notebooks to see if its possible. You r solution seems to work only if you have data in sql database and not in lakehouse.

@DataVerse_Academy 5 ай бұрын

Yes it will work for databases only. If you want to read incremental data from a lakehouse, you need to use notebook for that.

@paulmaksimovic9235 2 ай бұрын

Dont query the lakehouse - query the lakehouse sql endpoint as a sql connection. You can even use the sql endpoint to create a purpose made view

@moeeljawad5361 19 күн бұрын

@@paulmaksimovic9235 i think he will not be able to update the date_load in a table in a lakehouse, right?

@ryanabbey8880 5 ай бұрын

where did you handle an update process? PS you don't need to create the Set Variable steps, just use the item(). instead of where you're using the variable, while cost of a set variable is low, you're still using unnecessary cost

@DataVerse_Academy 5 ай бұрын

To handle updates, you can further create a procedure in data warehouse. In that you can write merge statement. Update handling is not available in the data pipeline yet.

@DataVerse_Academy 5 ай бұрын

Using set variable, I tried to simplify the things so that end user can understand what exactly we need to do for incremental load.

@ryanabbey8880 5 ай бұрын

@@DataVerse_Academyindeed... I came here from what I assume is your website (can't remember actual site) in which it stated the video shows how to do updates Inserts only is pretty impractical, don't think I've ever worked somewhere where only inserts is required so how MS thought this was a good tool, I don't know