Microsoft

Azure Speaker

MissionTech Media

Founder

Azurelib Academy

Founder & CEO

YASH Technologies

Technical Architect

Cognizant

Senior Software Engineer

Tata Consultancy Services

For collaboration, brand promotion and tech event speaking contact at:  azurelibblog@gmail.com

Hi, I'm Deepak Goyal, a certified Big data, and Azure Cloud Solution Architect.


I have 15+ Years of experience in the IT industry and 12+ Years of experience in Big data world.

I was among the few who has worked on Hadoop Big data analytics (since the Year 2011) before the popular advancement and adoption of Public cloud providers like AWS, Microsoft Azure, or Google Cloud Platform (GCP)

I help businesses to define the data-driven architecture and make robust data platform over the cloud to scale up their business.

Writing about Microsoft Azure technologies is one of my favorite works outside the office. 

I help people to understand cloud concepts and technologies like Azure Data Factory, Azure DataBricks, Apache Spark, Azure Synapse Analytics, Azure Key Vault, Encryption Decryption, Azure Blob Storage, Azure monitor, logging, Snowflake cloud data warehouse, Fivetran and many more complex tools and technologies.

I am a famous Azure blogger, my blog ranks number 1 on google search for more than 100+ keywords. 

The aim of this blog website is to share my expertise and experience as SME, to help people, learn by tutorials bundled with my personal experience, crack interviews, get their dream job and elevate themselves to the next level without paying anything.

I am a Youtuber too having more than 2K+ subscribers, who make videos on technical content like Hadoop, Mapreduce, pySpark, python, Snowflake, and many more.
 
Here on Linkedin as well,  I talk and write about Azure Data engineer, Azure certifications like Az-900, DP-203 study guide, DP-900, Az-104, Az-305, also solves people's technical queries and challenges.
 
In a nutshell, I am someone who spends a lot of his time working and talking about technology.


If you ever wonder about my work then you MUST check out 👇
- azurelib.com
- check my Youtube channel at @ItSkillsUpgrade


Feel free to hit me up in the LinkedIn DM, or simply 

send "Hi" to  azurelibblog@gmail.com


Thank you,
Deepak Goyal


**DISCLAIMER: All activity on this platform represents solely my own opinions and is not in any way, shape, or form, a representation of my current or past employers **

Deepak Goyal

I am launching something BIG and it’s 100% FREE.

After months of planning, I’m excited to announce a FREE 30-Day Azure WhatsApp Learning Program built for beginners, students, Az-900, DP-900 aspirants and anyone curious about the future of tech.

 What you’ll get for 30 days:

1. Daily 1-minute Azure videos (simple, powerful explanations)
2. Micro-lessons delivered to your WhatsApp
3. Daily quiz graphics to test your knowledge
4. Covers ALL essentials of Azure Fundamentals (AZ-900)
5. Covers ALL data concepts for Data Fundamentals (DP-900)
6. A friendly WhatsApp learning community

Who is this for?

1. Working professionals & job seekers
2. Cloud beginners
3. IT and non-IT professionals
4. Anyone preparing for Azure certifications
5. Anyone who wants to learn Azure in a simple and engaging way

Starting date: 19 Nov 2025

Want to join the FREE program?

1. Type “I’M IN” in comments and I will share link!
2. Or DM me “Azurelib” to get added instantly.

Let’s learn Azure one minute at a time.

Let’s grow together.

PS: First ever free WhatsApp based course. Don't miss it.

Here is the link: https://lnkd.in/d4DwKZme

𝗢𝗻 𝗮 𝗠𝗶𝘀𝘀𝗶𝗼𝗻 𝘁𝗼 𝗺𝗮𝗸𝗲 𝟭𝟬𝟬+ 𝗔𝘇𝘂𝗿𝗲 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝗶𝗻 𝗻𝗲𝘅𝘁 𝟰𝟱 𝗗𝗮𝘆𝘀

🇮🇳 A Truly Honoured Moment for Me 🙏

This time in Gangtok with the Government of Sikkim.

This week, I had the privilege to be invited by the Ministry of Electronics and Information Technology, Government of India (GoI) to conduct a 3-day AI & ML Workshop for the Government of Sikkim officials, in partnership with NeGD

Special thanks to the entire IT department of Govt of Sikkim. 

From fundamentals of Python to cutting-edge GenAI & ML applications,
 
I trained officers to not just understand AI, but apply it in real governance.

And I must say:

 - When Government starts focusing on AI,
 - You know India is truly getting future-ready!

Just a few years ago, I was creating LinkedIn posts from a small room.

Today, I’m getting the opportunity to train the people shaping India's digital transformation.

It’s not just about tech, It’s about impact.

To all the self-learners, dreamers, and hustlers reading this,

Keep building. Keep teaching. Keep giving back.

The world is watching. 

Join my WhatsApp channel to learn AI for Free: https://lnkd.in/dyYvqpJW

Why do employees want WFH or hybrid work models?

1. Because their parents are aging.
2. Because they are parents to their only child.
3. Because they want to spend more hours with their wife than with stranger flat mates.
4. Because they want an afterlife with friends in their hometown.
5. Because they want to save money and invest rather than spend it all on survival.
6. Because they want to avoid getting stuck in traffic and attend meetings through the spare laptop.

There's a compulsion for employees to work on-site by coming down to the office with strict log-in and log-out criteria.
Also, employees are forced to attend meetings with overseas teams/clients from their homes, using their personal laptops and data when needed.

What's the point behind this?

Why does location matter if employees deliver work without impacting quality and productivity?

In the so-called perfect corporate world with luxury salary packages, there are only processes and protocols—only for the sake of it, with not much sense!

post credit: Dr. Sakshi Khandelwal

One of the best post I came across today.

This is a powerful ChatGPT feature that every professional should set up today. 

Now you run this manually every day or set it as schedule task in ChatGPT to get about info about latest job posted.

This can run even on the free version on ChatGPT.

Example prompt in the snapshot below. Edit it based on your role, location, and preferences.

The more specific you are, the sharper the results.

PS: Adding the exact prompt in the comment to copy and paste.

Before start: I am not prepared for interview

After 1st interview: Failed, need to learn

After 5th interview: I know most of questions

After 7th interview: I got an offer

After 10th interview: I can clear any interview.

This is the journey for every normal IT professional.

Only thing that is stopping you is, not Starting

Start your journey before it's too late.

ADF Practice Questions:

Scenario 1: Data Transformation Pipeline
Scenario: Azurelib e-commerce collects sales data from multiple regional databases (SQL and NoSQL). The data needs to be cleaned, transformed, and stored in Azure Data Lake for analysis. The pipeline must also check the data’s integrity before loading it into the Data Lake. If data is incomplete or contains errors, it should be sent to a different storage location for reprocessing.

Q1: How would you design an Azure Data Factory pipeline to handle this scenario? Explain which activities you would use and how you would manage errors.

Scenario 2: Copying Data from On-premises to Azure
Scenario: Azurelib retail business has a legacy on-premises SQL Server database containing product and inventory data. The company wants to migrate this data to Azure SQL Database on a daily basis for reporting and analytics. The pipeline should minimize downtime and avoid impacting the on-premises server’s performance.

Q2: How would you design a pipeline in Azure Data Factory to copy this data from on-premises SQL Server to Azure SQL Database? Which ADF components would you use to ensure minimal downtime?

Scenario 3: Parameterized Pipelines
Scenario: You are working for an Azurelib e-commerce company that collects product reviews from different platforms daily. Each platform has a different API endpoint for data retrieval, and you need to ingest this data into Azure Data Lake. The process must be automated so that the pipeline dynamically fetches data based on the platform being processed.

Q3: How would you implement a parameterized pipeline in ADF to dynamically handle multiple data sources? Which parameters and activities would you configure?

Scenario 4: Data Lake Partitioning by Date
Scenario: Your organization stores large amounts of transactional data in Azure Data Lake, and the data is loaded daily from various sources. To improve query performance, you are tasked with partitioning the data in Azure Data Lake based on the date of the transaction.

Q4: How would you configure an ADF pipeline to partition data in Azure Data Lake by date? Which ADF activities and transformations would you use to achieve this?

Scenario 5: Failure Handling and Pipeline Monitoring
Scenario: You have set up a data pipeline that processes customer orders and loads them into Azure SQL Database. Sometimes, due to network issues or data corruption, the pipeline fails mid-execution. The business needs to be notified immediately if the pipeline fails, and the pipeline must be automatically retried a few times before stopping completely.

Q5: How would you configure failure handling and monitoring for this pipeline? What features of ADF would you use to send alerts and implement retries in case of failures?

Do share and follow Deepak Goyal for more.

Back when we were younger, this advice felt like gold:

Just work smart, not work hard

But now, it is not.

Because in the real world, everyone is smart.

- Everyone has access to ChatGPT
- Free resources, cheat sheets, mentors.
- Most common tips and tricks

So, what separates those who grow?

- Who doubles their CTC
- Who switched to that dream company

It’s not just a smart brain.

- Its practice for hours and hours
- It’s an effort after office hours.
- It’s staying up late, not scrolling, but studying.
- It's getting up after every fall
- It’s applying for 50 jobs and still showing up with energy for the 51st
- It’s building a habit when no one is clapping for you yet.

Yes, you’ll feel behind sometimes.
Yes, rejection will hurt.
Yes, it’s hard to push through when there’s no instant reward.

But hear this clearly:

- The world is full of smart people.
- Very few are consistent.
- Even fewer are unstoppable.

So if you’re tired of hearing: "We’ll get back to you"

Then stop relying only on strategy. Start showing up with fire.

Your next growth jump won’t come from working smarter.
It will come from working harder and outsmarting your competitors.

View newsletter: Mastering Data, Cloud and AI

If you're running Databricks in production, I want you to open your cloud billing dashboard right now. Look at your compute costs from last month. Now

Open article: How to Cut Your Databricks Costs by 40% Without Migrating Anything by Deepak Goyal • 5 min read

How to Cut Your Databricks Costs by 40% Without Migrating Anything

I once asked a friend,
“Why are you still in the same job for 8 years?”

He smiled and said,
“It’s stable. I know what I’m doing. No pressure, no surprises.”

But here’s what I noticed…

- Same job.
- Same tools.
- Same complaints.
- No new learning.
- No interviews.
- No growth.

He wasn’t building a career 

He was living the same 6 months over and over again.

And honestly? He’s not alone.

A lot of professionals get stuck in “comfort.”

They avoid change because it feels risky.

But here’s the truth:
Staying stuck is the biggest risk.

If you want something new a better role, higher pay, new challenges 

you have to walk a different path.

Learn.
Apply.
Fail.
Try again.

Because one day you’ll thank yourself…
for not settling.

🚀 Want to switch to a high-growth career in Azure Data Engineering?
 
I’m hosting a free masterclass where I’ll guide you through the roadmap and answer your 1:1 questions.

Reserve your seat now → https://lnkd.in/diuma7B8

WhatsApp: +91 93922 72173

Wavicle Data Solutions

Lead Data Engineer

LinkedIn

LinkedIn Learning Instructor

Globant

Senior Data Engineer

CRISIL Limited

Senior Analyst - Data Engineer

Quantiphi

Data Engineer

System Engineer

Assistant System Engineer

Assistant System Engineer - Trainee

InsideSherpa

KPMG Data Analytics Consulting Virtual Internship

Monisha Enterprises

•	Data mining and Extraction Transformation Loading using R programming.
•	Data cleaning and processing for Data analysis done using Python using NumPy, pandas, SciPy, Scikit. Data modelling and prediction was done using algorithms – Logistic Regression, Time Series Forecasting, Clustering and Classification.
•	Data Visualization done using Tableau for generating reports to enhance the productivity of the products.
•	Built a Data Warehouse on MSSQL Server for ERP System of the enterprise to organize the data for future processing.

Data Analyst Intern

Open to Collaborate | Storyteller | Lead Data Engineer@Wavicle| Linkedin Top Voice 2024 | Globant | Linkedin Learning Instructor | 2xGCP & AWS Certified | LICAP'2022

Data Engineer with 7+ years of experience working on data engineering, analysis, and modelling projects for various domains, such as banking, healthcare, sales, and e-commerce. I leverage my strong statistical and analytical ability to explore business ideas and provide innovative solutions. 

Skilled with technologies and strong intellect with enthusiasm as an avid learner with challenging opportunities. I’m working as a LinkedIn Learning Instructor to bring change as a data evangelist.

Post Graduated in Master of Technology in Data Science and Engineering from Birla Institute of Technology and Science, Pilani in 2023, where I learned advanced concepts and techniques in data science and engineering, machine learning, cloud computing, and visualization. 

I hold multiple certifications in GCP, AWS, and Azure, and I enjoy working with cloud technologies and big data platforms.

I am passionate about data science and women empowerment, and I have been recognized as the 
- Linkedin Top Voice 2024 
- Data Science and Women Empowerment Thought Leader by Global AI Hub. 

I am also a proud participant of the LinkedIn Creator Accelerator Program 2022, where I share my insights and experiences with the data science community. 

I am open to collaborate and share ideas, or explore various opportunities in the data field.

Pooja Jain

73% of data pipeline failures happen because of dependency issues, not bad code.
Cron jobs don't care if yesterday's data never arrived. They'll happily run on empty tables and produce garbage.

Airflow? It checks, retries, alerts, and refuses to cascade your failure downstream.

→ Beyond scheduling Airflow gives an important feature of 𝗗𝗔𝗚𝘀(𝗗𝗶𝗿𝗲𝗰𝘁 𝗔𝗰𝘆𝗰𝗹𝗶𝗰 𝗚𝗿𝗮𝗽𝗵𝘀), that helps to monitor, retry and gives flexibility to organize pipelines with minimum/less code.

🤔 Data Engineers often misinterpret Airflow just as an orchestration tool.

Apache Airflow is an open-source platform designed to programmatically author, schedule, retry and monitor workflows. 

🎼Think of it as the "conductor of an orchestra", where each musician (your data tasks, like data extraction, transformation, loading, or model training) knows when to play, what to play, and what happens if they make a mistake.

Most data engineers automate the wrong things at the wrong time.

Here's the framework I use after 8 years of building production systems:
✅ AUTOMATE WHEN: 
→ Task runs daily/weekly 
→ Human errors cause outages 
→ Work blocks other priorities
→ Team growth = more manual work
Examples: Reports, schema checks, alerts

❌ DON'T AUTOMATE WHEN: 
→ Task happens quarterly 
→ Requirements change weekly 
→ Process isn't understood yet 
→ Manual steps reveal insights

My rule: If it’s done 3+ times, script it; 10+ times, automate it; fails 5+ times, redesign it.
Automate what matters, when it matters—not everything!

Airflow isn’t just about running tasks.

🕑 It’s about building trustworthy, scalable, and observable pipelines that run reliably at 2am — even when you’re not watching.

Airflow gives structure to your chaos.
DAGs give clarity to your pipelines. 
That’s why DEs love them ❤️

Real Example: 
Instead of: 
❌ Cron jobs that fail silently 
❌ Manual dependency management
❌ No visibility into failures
You get: 
✅ Visual workflow monitoring 
✅ Automatic failure notifications
✅ Smart task scheduling 
✅ Easy debugging & restarting

Here's an amazing Airflow cheatsheet with some fundamentals concepts and interview questions to prepare for data engineers. 👇

Carousel Credits -  Futurense.com

Willing to learn more, here's the link to Astronomer free learning path - https://lnkd.in/g8-EWBda

Also, level up with Marc Lamberti's Udemy course on Airflow 3 - https://lnkd.in/gwArwaME

taplio

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The Battle

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Pooja Jain

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Engagements

Likes

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