Mastering Azure Data Engineering with Python

This book is a comprehensive guide to building scalable and secure data solutions using Azure and Python. It covers the following key areas:

📌 Chapter 1: Introduction to Azure Data Engineering – Overview of Azure tools, why Python is essential, and the core technologies used.

📌 Chapter 2: SQL for Azure Data Engineering – Writing optimized SQL queries, indexing strategies, and automating SQL procedures with Python.

📌 Chapter 3: Python for Data Engineering – Automating data pipelines, integrating APIs, and advanced data manipulation techniques.

📌 Chapter 4: Big Data Handling with PySpark – Managing DataFrames and RDDs, optimizing transformations, and improving performance with partitioning.

📌 Chapter 5: Building ETL Pipelines with Azure Data Factory – Creating, debugging, and automating real-time ETL workflows.

📌 Chapter 6: Scalable Data Processing with Azure Databricks – Using notebooks, clusters, and optimizing Spark queries for large-scale data.

📌 Chapter 7: Advanced Analytics with Azure Synapse – Query optimization, managing data pools, and automating analytics workflows.

📌 Chapter 8: Data Storage and Security in Azure – Managing Data Lake Storage, implementing security best practices, and optimizing file formats.

📌 Chapter 9: Securing Data with Azure Key Vault – Managing secrets, encrypting data, and automating access control.

📌 Chapter 10: End-to-End Analytics with Microsoft Fabric – Using Python for OneLake, Data Factory, and implementing analytics pipelines.

📌 Chapter 11: Best Practices and Industry Use Cases – Performance tuning, security compliance, and real-world case studies.

📌 Chapter 12: Conclusion and Career Guidance – Future of data engineering, certification resources, and career paths.

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You can also see different articles from me:

https://www.linkedin.com/pulse/maximizing-your-linkedin-presence-types-valuable-shanthi-kumar-v–8wwsc/?trackingId=9yuYMUEMSIysudnbfIC1pw%3D%3D

https://www.linkedin.com/pulse/secret-building-strong-linkedin-following-key-reasons-m8ekc/?trackingId=%2F2q6R2TDQBGTKrALBtoNZQ%3D%3D

https://www.linkedin.com/pulse/mastering-linkedin-2025-key-algorithm-changes-how-shanthi-kumar-v–xn7qc/?trackingId=wui%2FDXgb%2FnQ5CHgsc2Vcmw%3D%3D

The LinkedIn algorithm in 2025 has undergone significant updates aimed at enhancing user experience and content visibility. Here are the key features and changes:

Core Principles of the Algorithm

• Relevance: The algorithm prioritizes content that aligns with users’ professional interests and relationships, ensuring that the most pertinent posts appear first in their feeds14.
• Engagement: Content that generates high engagement—through likes, comments, and shares—receives increased visibility. The algorithm favors posts that encourage meaningful interactions among users12.
• Personalization: The algorithm customizes the news feed based on users’ past actions, interests, and connections, providing a tailored experience13.

Major Changes in 2025

• Focus on Niche Content: The algorithm now emphasizes content relevance to specific niches, directing publications to audiences most likely to engage with them13.
• Value of First-Degree Connections: Posts from first-degree connections are prioritized, fostering exchanges within users’ immediate networks and strengthening professional ties24.
• Encouragement of Constructive Conversations: Content that stimulates deep discussions is favored over superficial interactions, promoting richer engagement13.
• Recognition of Expertise: Contributions from recognized experts are valued more highly, highlighting the importance of sharing in-depth knowledge and professional experience14.

Factors Influencing Content Visibility

• Quality of Content: High-quality, engaging posts that provide value are essential for visibility. Avoiding external links in posts is advised; instead, they should be placed in comments12.
• Engagement Signals: The likelihood of engagement based on past interactions plays a crucial role in determining post ranking. Posts that receive quick engagement tend to rank higher26.
• Network Interactions: Actively engaging with one’s network—through comments and shares—can enhance the visibility of both profiles and publications13.

Conclusion

In summary, the LinkedIn algorithm for 2025 emphasizes relevance, engagement, and personalization while prioritizing quality content from first-degree connections. Users are encouraged to create meaningful interactions and share expert knowledge to maximize their visibility on the platform.

For more detailed insights, you can refer to the following sources:

• MirrorProfiles
• Social Champ
• Metricool
• StraightIn

Citations:

1. https://mirrorprofiles.com/en/algorithme-linkedin-2025-comment-fonctionne-t-il/
2. https://www.socialchamp.com/blog/linkedin-algorithm/
3. https://metricool.com/linkedin-algorithm/
4. https://straight-in.com/blog/how-the-linkedin-algorithm-works-in-2025/
5. https://sproutsocial.com/insights/linkedin-algorithm/
6. https://100poundsocial.com/blog/linkedin/linkedin-algorithm/
7. https://www.linkedin.com/posts/mattnavarra_how-linkedins-algorithm-works-in-2025-youll-activity-7303106971757346816-V3Z2
8. https://www.linkedin.com/pulse/mastering-linkedin-algorithm-your-guide-maximising-reach-grant-w-cook-v3fzc

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The LinkedIn 2025 algorithm prioritizes content from first-degree connections to enhance the relevance of users’ feeds. This change ensures that posts from immediate connections—such as colleagues, collaborators, and individuals users have interacted with—are displayed more prominently. Here are the key details:

• Feed Prioritization: Posts from first-degree connections appear first in users’ feeds, as LinkedIn values content shared within direct professional networks over third-degree or viral content13.
• Engagement and Relevance: The algorithm emphasizes meaningful interactions within first-degree networks, such as comments and shares, which foster deeper connections and discussions34.
• Quality Connections: LinkedIn encourages users to maintain high-quality connections that contribute valuable professional content, further enhancing the feed’s relevance3.

This shift aligns with LinkedIn’s goal of creating a professional environment where users engage with trusted networks and expertise-driven content134.

Citations:

1. https://expandi.io/blog/linkedin-algorithm-changes/
2. https://www.searchenginejournal.com/linkedin-algorithm/424098/
3. https://metricool.com/linkedin-algorithm/
4. https://tinuiti.com/blog/paid-social/linkedin-algorithm/
5. https://buffer.com/resources/linkedin-algorithm/
6. https://sproutsocial.com/insights/linkedin-algorithm/
7. https://www.shopify.com/blog/linkedin-algorithm
8. https://contentstudio.io/blog/linkedin-algorithm

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Content that performs best with first-degree connections on LinkedIn typically focuses on fostering professional relationships, sharing valuable insights, and encouraging meaningful engagement. Here are the key types of content that resonate well:

• Personalized Updates: Sharing personal achievements, career milestones, or updates about your professional journey helps strengthen relationships with immediate connections14.
• Industry Insights: Posts that provide valuable information, such as trends, news, or expert analysis in your field, are highly engaging for first-degree connections interested in staying informed47.
• Interactive Content: Asking questions, initiating discussions, or creating polls encourages direct engagement and interaction among your connections14.
• Storytelling: Sharing relatable anecdotes or professional experiences that highlight lessons learned or challenges overcome can foster deeper connections and engagement7.
• Collaborative Posts: Tagging first-degree connections in posts or mentioning them in comments helps boost visibility and interaction within your immediate network4.

These content types align with LinkedIn’s algorithm, which prioritizes posts that generate meaningful interactions among first-degree connections.

Citations:

1. https://www.lemlist.com/blog/linkedin-1st-2nd-3rd-meaning
2. https://linkedprospect.com/master-your-first-degree-linkedin-connections/
3. https://www.searchenginejournal.com/linkedin-algorithm/424098/
4. https://dripify.io/linkedin-1st-2nd-3rd-degree-connections/
5. https://salesflow.io/the-different-degrees-of-connections-on-linkedin-what-do-they-mean/
6. https://www.linkedhelper.com/blog/1st-2nd-3rd-linkedin/
7. https://neilpatel.com/blog/linkedin-post/
8. https://blog.linkboost.co/what-is-the-1st-2nd-3rd-in-linkedin-and-how-to-get-more-connections/

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