Incremental Load- Type 1(Part-5) - End to End Azure Data Engineering Project using Microsoft Fabric

Unlock the power of Bing News Data Analytics in our latest tutorial, where we embark on a comprehensive End-to-End Azure Data Engineering Project utilizing Microsoft Fabric! 🌐
The Topics covered in this Project are,
1. Data Ingestion from Bing API using Data Factory: Learn how to seamlessly pull in data from external sources, setting the foundation for your analytics project.
2. Data Transformation using Synapse Data Engineering: Dive into the process of shaping and refining your raw JSON data to a curated Delta Table, including techniques like incremental loading to keep your processes efficient.
3. Sentiment Analysis using Synapse Data Science: Uncover insights hidden within the news description by predicting the sentiment of the news classified as Positive, Negative or Neutral.
4. Orchestration using Data Factory via pipelines: Discover the art of orchestrating your data workflows, ensuring smooth and efficient operations.
5. Data Reporting using Power BI: Visualize your data in a compelling and actionable manner, empowering stakeholders with valuable insights.
6. Configuring Alerts using the Data Activator: Stay ahead of potential issues by setting up alerts and notifications within your Power BI visuals using a new tool called Data Activator.
7. End to End Pipeline Testing: The complete flow will be tested right from the data ingestion to the data transformation and until the report gets updated with the incoming new data to Validate the integrity and performance of your pipelines, ensuring reliability and accuracy.
This project revolves around Bing News Data Analytics, a practical application that involves ingesting news data daily and generating insightful reports. By walking through each step in a simplified manner, I aim to make Azure Data Engineering accessible to all enthusiasts, regardless of their background.
- - - Book a Private One on One Meeting with me (1 Hour) - - -
www.buymeacoff...
- - - Express your encouragement by brewing up a cup of support for me - - -
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- - - Other useful playlist: - - -
1. Microsoft Fabric Playlist: • Microsoft Fabric Tutor...
2. Azure General Topics Playlist: • Azure Beginner Tutorials
3. Azure Data Factory Playlist: • Azure Data Factory Tut...
4. Databricks CICD Playlist: • CI/CD (Continuous Inte...
5. Azure Databricks Playlist: • Azure Databricks Tutor...
6. Azure End to End Project Playlist: • End to End Azure Data ...
7. End to End Azure Data Engineering Project: • An End to End Azure Da...
- - - Let’s Connect: - - -
Email: [e-mail]
Instagram: mrk_talkstech
- - - About me: - - -
Mr. K is a passionate teacher created this channel for only one goal "TO HELP PEOPLE LEARN ABOUT THE MODERN DATA PLATFORM SOLUTIONS USING CLOUD TECHNOLOGIES"
I will be creating playlist which covers the below topics (with DEMO)
1. Azure Beginner Tutorials
2. Azure Data Factory
3. Azure Synapse Analytics
4. Azure Databricks
5. Microsoft Power BI
6. Azure Data Lake Gen2
7. Azure DevOps
8. GitHub (and several other topics)
After creating some basic foundational videos, I will be creating some of the videos with the real time scenarios / use case specific to the three common Data Fields,
1. Data Engineer
2. Data Analyst
3. Data Scientist
Can't wait to help people with my videos.
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Please Subscribe: / @mr.ktalkstech

[@90harvinder]

I’m in awe of your teaching style. You explain the advanced topics with such an ease that anybody can understand.

[@sharaniyaswaminathan8760]

I second this :) Thank you Mr. K

[@mr.ktalkstech]

Thank you so much :)

[@VijayTagad]

Your videos are very engaging, thanks to you. One suggestion, sir: you can use PPT slides to minimize your animation editing efforts, allowing you to create more content in a short span of time. Looking forward to the next part ........

[@TheLeads]

Just surprised that isn't there a function to check if the table already exists or not and then doing the merge if exists. It's not looking like a good practice of failing it deliberately everytime and writing the core logic inside an exception block. 🙂

[@Warrior_praful]

It’s because the condition-based approach offers a balance between flexibility and performance in a distributed environment like Spark. It ensures that you have control over when and how you check for the existence of a table across various storage systems and formats.

[@Sgm_is_here]

In this approach while doing the incremental sync, if we have millions of records exist in source , is it feasible to do the same approach?
In this approach on daily basis we will be keep checking the entire website or database to see if anything updates. if we have a huge data from source it will be time consuming process I guess.

[@MexiqueInc]

Hello, just finished this section . Wanna thank you for your valuable efforts. As a suggestion, please include the code as a link on the upcoming videos. I'm follower since many months ago. Regards

[@manibaddireddy5477]

Can you please do a real time project using Kafka

[@raymondfloyd6397]

✋ "Promosm"

[@starstar6642]

Can u provide worksupport for ADF

[@davidkiplangat2590]

Hey, This is good work. Much appreciated.

[@mr.ktalkstech]

Thank you so much :)