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

𝟭𝟬𝟬% 𝗚𝗨𝗔𝗥𝗔𝗡𝗧𝗘𝗘𝗗 𝗧𝗢 𝗦𝗢𝗟𝗩𝗘 𝗬𝗢𝗨𝗥 𝗕𝗜𝗚𝗚𝗘𝗦𝗧 𝗣𝗥𝗢𝗕𝗟𝗘𝗠

“𝗜 𝗸𝗻𝗼𝘄 𝗣𝘆𝘁𝗵𝗼𝗻 𝘀𝘆𝗻𝘁𝗮𝘅… 𝗯𝘂𝘁 𝗜 𝗱𝗼𝗻’𝘁 𝗸𝗻𝗼𝘄 𝗵𝗼𝘄 𝘁𝗼 𝗯𝘂𝗶𝗹𝗱 𝗹𝗼𝗴𝗶𝗰.”

If this sounds familiar, 𝘆𝗼𝘂 𝗮𝗿𝗲 𝗻𝗼𝘁 𝗮𝗹𝗼𝗻𝗲.

Most people fail in coding 𝗻𝗼𝘁 𝗯𝗲𝗰𝗮𝘂𝘀𝗲 𝗼𝗳 𝘀𝘆𝗻𝘁𝗮𝘅,

but because no one teaches 𝗵𝗼𝘄 𝘁𝗼 𝗧𝗛𝗜𝗡𝗞.

🔥 𝗧𝗵𝗮𝘁’𝘀 𝗲𝘅𝗮𝗰𝘁𝗹𝘆 𝘄𝗵𝗮𝘁 𝗜’𝗺 𝗳𝗶𝘅𝗶𝗻𝗴.

I’ve started a 𝗙𝗥𝗘𝗘 𝗟𝗜𝗩𝗘 𝗕𝗢𝗢𝗧𝗖𝗔𝗠𝗣 where you’ll learn:

 ✅ 𝗛𝗼𝘄 𝘁𝗼 𝗯𝘂𝗶𝗹𝗱 𝗹𝗼𝗴𝗶𝗰 𝘀𝘁𝗲𝗽-𝗯𝘆-𝘀𝘁𝗲𝗽
 ✅ 𝗛𝗼𝘄 𝘁𝗼 𝗰𝗼𝗻𝘃𝗲𝗿𝘁 𝗽𝗿𝗼𝗯𝗹𝗲𝗺𝘀 𝗶𝗻𝘁𝗼 𝗰𝗼𝗱𝗲
 ✅ 𝗛𝗼𝘄 𝗿𝗲𝗮𝗹 𝗽𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗲𝗿𝘀 𝘁𝗵𝗶𝗻𝗸
 ✅ 𝗣𝘆𝘁𝗵𝗼𝗻 𝗹𝗼𝗴𝗶𝗰 — 𝗻𝗼 𝗰𝗼𝗻𝗳𝘂𝘀𝗶𝗼𝗻, 𝗻𝗼 𝗳𝗮𝗻𝗰𝘆 𝘄𝗼𝗿𝗱𝘀

- 𝗡𝗼 𝘁𝗵𝗲𝗼𝗿𝘆 𝗼𝘃𝗲𝗿𝗹𝗼𝗮𝗱. 𝗡𝗼 𝗽𝗮𝗶𝗱 𝘂𝗽𝘀𝗲𝗹𝗹.
- 𝗝𝘂𝘀𝘁 𝗽𝘂𝗿𝗲, 𝗽𝗿𝗮𝗰𝘁𝗶𝗰𝗮𝗹 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴.

📌 𝗧𝗵𝗶𝘀 𝗶𝘀 𝗳𝗼𝗿 𝘆𝗼𝘂 𝗶𝗳:
- You know Python basics but feel stuck
- You freeze when given a new problem
- You want to crack interviews, projects, or real-world use cases

⏳ 𝗟𝗶𝗺𝗶𝘁𝗲𝗱 𝘀𝗲𝗮𝘁𝘀 (to keep it interactive)
 🎓 𝟭𝟬𝟬% 𝗙𝗥𝗘𝗘
🔗 𝗘𝗻𝗿𝗼𝗹𝗹 𝗵𝗲𝗿𝗲: Enroll for free: https://lnkd.in/dVYrJeEp


PS: 𝗦𝘁𝗼𝗽 𝗺𝗲𝗺𝗼𝗿𝗶𝘇𝗶𝗻𝗴 𝗰𝗼𝗱𝗲. 𝗦𝘁𝗮𝗿𝘁 𝘁𝗵𝗶𝗻𝗸𝗶𝗻𝗴 𝗹𝗶𝗸𝗲 𝗮 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿.

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

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 2025, 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

Learn, Earn or Leave

Loyalty is beautiful… until you realize  
it was never mutual.

Your company will replace you faster than you can say "team player"

The company?  
It’s just business.  
Treat it accordingly. 🛡️

Agree?

No alternative text description for this image

Without governance, your data is a 10-lane highway with no traffic lights.

Everyone's driving. Nobody knows the rules. Accidents are inevitable.

Why does it Matters?
Think traffic system for organizational data.
 • Data flows smoothly, safely, smartly
 • Everyone knows their lane
 • Decisions made with confidence
 • Teams drive results, not fix messes

Without traffic lights, you don't get speed; you get gridlock and crashes.

🔑 Your Role as a Leader
Strategy & Oversight:
 → Champion governance (sponsorship + resources)
 → Set the tone for responsible data use
 → Hold leaders accountable for data quality
 → Not your job: Managing day-to-day data operations

👥 Who Does What ?(Simplifying the roles)
 • Chief Data Officer: Sets data strategy
 • Data Security Officer: Shields from risk
 • Head of Governance: Enforces data rules
 • Data Quality Manager: Validates accuracy

 → Data Owners: Accountable for specific datasets
 → Data Stewards: Maintain quality and access
 → Product Owners: Align data with user needs
 → Data Custodians: Handle storage and security

Here's to quick start and win early -
Reflect: Where do you rely on data today? Where do you trust it?
Clarify: Which outcomes matter most?
Identify: Who owns critical data decisions?

But, Why Now?
AI is scaling. Without governance, pilots stall and ROI evaporates.
Competition moves fast. Trusted data = speed advantage.
Regulations tighten. Fines and reputation hits are expensive.

𝘎𝘰𝘰𝘥 𝘨𝘰𝘷𝘦𝘳𝘯𝘢𝘯𝘤𝘦 𝘪𝘴𝘯'𝘵 𝘣𝘶𝘳𝘦𝘢𝘶𝘤𝘳𝘢𝘤𝘺—𝘪𝘵'𝘴 𝘵𝘩𝘦 𝘣𝘭𝘶𝘦𝘱𝘳𝘪𝘯𝘵 𝘧𝘰𝘳 𝘈𝘐 𝘵𝘩𝘢𝘵 𝘢𝘤𝘵𝘶𝘢𝘭𝘭𝘺 𝘥𝘦𝘭𝘪𝘷𝘦𝘳𝘴.

My final thoughts:
If 𝗱𝗮𝘁𝗮 is the fuel and 𝗔𝗜 is the engine,
𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 is the steering wheel.
Without it, speed means nothing.

Refer this to explore what Atlan says about Data Governance pillars in 2026 -https://lnkd.in/dAMTYJGy

Data pipelines are evolving from the "copy-paste" era to the "access-anywhere" era. Are you evolving with them?

At its core, data pipelines answers one thing -
How does data moves from "happened" to "decision made"?

Here's how the evolution looks like:
𝗘𝗧𝗟 (The Old Way) Extract → Transform → Load
 • Like preprocessing your groceries in the parking lot before bringing them inside
 • Great for strict governance, legacy systems
 • Slow. Rigid. Breaks on every schema change
 • Tools: Glue, Talend, NiFi

𝗘𝗟𝗧 (The Cloud Era) Load raw → Transform in warehouse
 • Load raw, transform in warehouse. Like, Dump groceries in fridge, prep later
 • Scales with cloud compute
 • Better, but still copying data everywhere
 • Tools: dbt, Snowflake, BigQuery

𝗖𝗗𝗖 (Real-Time Tax) Change Data Capture
 • Stream every database change via transaction logs
 • Captures inserts/updates/deletes from source. Near real‑time, low overhead
 • Perfect for fraud detection. Expensive for everything else
 • Tools: Debezium, AWS DMS

𝗦𝘁𝗿𝗲𝗮𝗺𝗶𝗻𝗴 (Over-Engineering Champion) 
 • Real‑time processing, no waiting. Just like Food truck serving as you arrive
 • Necessary for IoT, trading, Fraud and live dashboards
 • Overkill for your Monday morning dashboard
 • Tools: Kafka, Flink, Kinesis.

Enter 𝗭𝗲𝗿𝗼 𝗘𝗧𝗟: The "Why Are We Doing This?" Moment
The modern lakehouse game‑changer
One city library for everyone – no need to photocopy books.
Data lives in one place (lakehouse).
Query it directly with any engine. No copying.

🤔 How Modern Lakehouses Make This Real?

𝗢𝗽𝗲𝗻 𝗧𝗮𝗯𝗹𝗲 𝗙𝗼𝗿𝗺𝗮𝘁𝘀 (Iceberg, Hudi, Delta)
Think: Git for data. ACID transactions, time travel, schema evolution—on cheap object storage.

𝗦𝘁𝗼𝗿𝗮𝗴𝗲 ≠ 𝗖𝗼𝗺𝗽𝘂𝘁𝗲
Data sits in S3. Spark reads it. Snowflake queries it. Trino analyzes it. Same files. No copies. No vendor lock-in.

𝗡𝗮𝘁𝗶𝘃𝗲 𝗖𝗼𝗻𝗻𝗲𝗰𝘁𝗼𝗿𝘀
AWS Aurora → S3? Managed replication.
No custom Glue jobs. No 3 AM debugging.

What Changes for You?

You stop:
- Writing extraction code for the 47th time
- Maintaining Airflow DAGs that "mysteriously fail on Wednesdays"
- Explaining why reports are 6 hours delayed
- Paying for storage in four different systems

You start:
- Designing smart partitioning strategies
- Building dbt models where transformation actually matters
- Focusing on data quality, not data plumbing
- Solving business problems instead of pipeline problems

The Real Talk?

Zero ETL isn't "no data engineering." 
It's engineering that matters.
Traditional ETL won't vanish overnight—too much legacy infrastructure. 

But for new projects? Start lakehouse-first:
- Store once in open formats
- Let compute engines come to data
- Create copies only when necessary

Think of it this way: 
You wouldn't photocopy a book every time someone wants to read a different chapter. 
So why copy your data every time a new team needs access?

taplio

The Battle

Deepak Goyal

Pooja Jain

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Performance ScoreDeepak Goyal's LinkedIn Performance

Performance ScorePooja Jain's LinkedIn Performance

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taplio

The Battle

Deepak Goyal

Pooja Jain

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Deepak Goyal's LinkedIn Performance

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Performance ScoreDeepak Goyal's LinkedIn Performance