I am a seasoned Data Scientist/Analyst with a rich experience spanning two years in the field. Over the past year, I have proudly contributed my skills and expertise to the dynamic teams of both Data Science (Personalisation - ML) and Data Engineering at McAfee. My journey has been marked by a relentless pursuit of excellence and a passion for transforming data into meaningful, concrete insights.

My proficiency in SQL, Python, Spark, my ability to figure out a way around blockers on the go, and my decisiveness with sound reasoning has been the cornerstone of my success, enabling me to extract, analyze, and interpret data with precision. My adeptness in these tools has empowered me to spearhead feature engineering projects, playing a pivotal role in enhancing the value of data and optimizing its use for strategic decision-making.

One of my significant accomplishments includes being a key contributor to the establishment of a feature store at McAfee. 
As we all know, from start to end, 70% of time in most Machine Learning projects is spent on finding out correct POCs within the company, communicating with them to acquiring the correct data and also understanding it, predicting probable metrics to be obtained from it, and then performing the pre-processing. 
Developing a feature store involved a lot of Feature Engineering, gaining close familiarity with the raw data, understanding the business and performing a lot of SQL intricacies, not to forget a lot of internal communication. The objective was to cut down on the preprocessing time and provide Data Scientists 
with data they could rapidly build prototypes upon without having to worry about the entire logistics of how it came to be. The nature of this 'pre-processed' data was that it could support a lot of Data Science efforts, since this data captured the essential behavior of our customers. 

This innovative solution has not only streamlined workflows but has also facilitated the acceleration of data-driven innovation within the organization.

Motivated by my unwavering commitment to continuous growth and a thirst for knowledge, I am eager to expand my horizons into the realms of Data Engineering and Data Science. Drawing upon my foundation in analytics and my proficiency in key technologies, I am excited to take on new challenges and leverage my skill set to drive transformative insights and solutions.

In essence, my journey reflects a fusion of experience, technical prowess, and an unrelenting desire to create value from data.

Sidharth Kriplani

Senior Analyst @ Accenture | Helping Students & Beginners Break into Data Careers | 1:1 Coaching, Projects, & Career Roadmaps | 350+ placed | Open to collaborate| Youtuber

Sr. Analyst | Data Influencer | Educator | Career Coach & Mentor
Guiding aspiring analysts to break into the data field with clarity, confidence & real-world skills.

In 2019, I stepped into the world of Data Analytics—
❌ No technical background
❌ No connections
❌ No roadmap

Just pure perseverance and a commitment to learn.

Today, I make sure you don't have to walk that path alone.
Through years of mentoring and hands-on industry experience, I’ve helped 2000+ students transition into successful analytics careers—and the community continues to grow. 🚀

👨‍🏫 What I Do as a Career Coach & Mentor

🎯 Personalized career roadmaps for non-technical professionals entering analytics

📄 Resume revamps that highlight your transferable skills

🤝 1:1 job search coaching with practical, buzzword-free guidance

🎤 Interview preparation tailored to analytics roles

🌐 Access to a supportive community of career-changers

📢 Open for collaborations, workshops, speaking events & training sessions

🎓 Who I Help

🔄 Career switchers unsure where to begin

🎓 Students struggling to get noticed

💼 Professionals seeking growth in analytics

👥 Anyone from a non-tech background who wants to build a successful career in data

🤗 Individuals who want a supportive, consistent, growth-focused community

🤝 Let’s Connect

📩 Email: mk24sablani@gmail.com

🌏 For Australian students: https://emergimentors.com.au/dashboard

💬 Open for: collabs, speaker invites, orientation events, corporate seminars & workshops

Mukesh Sablani

𝐒𝐐𝐋 𝐂𝐡𝐞𝐚𝐭 𝐒𝐡𝐞𝐞𝐭 

Lost in the maze of SQL commands?
You’re not alone.

The secret isn’t memorising endless syntax.
It’s mastering the core concepts that power every data-driven decision.

Here’s your 𝐒𝐐𝐋 𝐂𝐡𝐞𝐚𝐭 𝐒𝐡𝐞𝐞𝐭 for Data Analysts

• SQL Database: Your data’s home base. Know how to create, manage, and optimize databases.

• SQL Constraints: Enforce rules for data accuracy and integrity. Primary keys, unique, NOT NULL - these aren’t just buzzwords; they protect your data.

• SQL Operators: The building blocks. Learn logical AND, OR, IN, NOT to craft precise queries.

• SQL Views: Virtual tables that simplify complex data. They save time and reduce errors.

• SQL Tables: The real data holders. Understand their design to improve query performance.

• SQL Joins: The heart of relational data. Master INNER, LEFT, RIGHT, and FULL joins to connect your datasets seamlessly.

• SQL Functions: Aggregate, scalar, window functions – use them wisely for advanced analytics.

• SQL Clauses: WHERE, GROUP BY, HAVING – filter and group data efficiently.

• SQL Indexes: Speed up retrieval. Knowing when and how to index is a game changer.

• SQL Stored Procedures: Automate repetitive tasks and encapsulate logic for reuse.

You don’t need every SQL trick.
You need the right ones applied with precision.

➡️𝐑𝐞𝐚𝐝𝐲 𝐭𝐨 𝐥𝐚𝐧𝐝 𝐲𝐨𝐮𝐫 𝐝𝐫𝐞𝐚𝐦 𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐬𝐭 & 𝐀𝐈 𝐫𝐨𝐥𝐞? 

𝐃𝐌 me for resume & LinkedIn optimization, hands-on portfolio building, targeted job strategies, mock interviews, and personalized mentorship - all designed to 𝐟𝐚𝐬𝐭-𝐭𝐫𝐚𝐜𝐤 𝐲𝐨𝐮𝐫 𝐝𝐚𝐭𝐚 & 𝐀𝐈 𝐜𝐚𝐫𝐞𝐞𝐫 𝐬𝐮𝐜𝐜𝐞𝐬𝐬

Follow Mukesh Sablani for more insights on Data Analysis

I am a Senior Analyst at Accenture with 5+ years of experience.
Here are 5 tips for aspiring Data analysts in 2026:

◄ Learn Python also
Python is the future, not just a trend.
Learn Pandas, NumPy, and basic scripting.
Companies want people who can code, not just click buttons.
This skill will help you stand out in interviews.

◄ Focus on AI automation and ETL processes
Learn how to automate boring tasks.
Understand ETL—Extract, Transform, Load data pipelines.
Use AI tools to save time on repetitive work.
Don't just copy code—understand how it works.

◄ Get comfortable with cloud tools
Learn AWS, Azure, or Google Cloud basics.
Know how to store and process data in the cloud.
Most companies are moving to cloud platforms.
Even basic knowledge gives you a huge advantage.

◄ Think like a business person
Every task you do should solve a real problem.
Show the value—how much time or money you saved.
Learn basic business terms like ROI, revenue, and growth metrics.

◄ Keep your communication simple and show your work
Simple solutions beat complex ones.
Always explain "why this matters" in your reports.
Share your projects online and be active on LinkedIn.
People hire those who share their knowledge.
–
P.S. I'm Mukesh Sablani, a Senior Analyst at Accenture.
Follow me for more tips on data and AI.
Repost if this helped you!

Hi Everyone ,
I want to share my Accenture interview experience for the Sr Decision Analyst 
Honestly, the interview was not easy — it was more focused on real practical knowledge of Power BI + SQL + Python and how you solve business problems.
So I’m sharing the important questions/topics that were asked

Accenture in India Sr Decision Analyst Interview Questions (Power BI + SQL + Python)

If you're preparing for Accenture Sr Decision Analyst / SrData Analyst roles, the interview is NOT basic. They ask advanced Power BI + SQL + Python + real business scenarios.

Here are the exact types of questions asked in interviews:
1) Advanced Power BI Questions
Star schema vs Snowflake schema
Row context vs Filter context
CALCULATE() in DAX (most important)
ALL vs ALLEXCEPT vs ALLSELECTED
Running Total / YTD / Rolling 3 months
USERELATIONSHIP (inactive relationship)
SUMX / RANKX (real use cases)
Query Folding (Power Query)
Import vs DirectQuery vs Composite
Incremental Refresh
RLS (Row Level Security)

2) Advanced SQL Questions
Window Functions (MOST asked)
ROW_NUMBER vs RANK vs DENSE_RANK
Top 3 records per group
Running total using OVER()
LAG / LEAD use case
Query Optimization
Indexing concept
Execution plan
CTE vs Temp table vs View

3) Python Questions (Automation + Analysis)
Pandas merge / join / concat
Handling missing values
GroupBy KPIs
Script to merge 100+ CSV files
Exception handling + logging
Automation using scheduler

4) Scenario-Based Questions
Dashboard slow – how will you optimize?
Numbers mismatch – how will you debug?
Stakeholder wants urgent delivery – how will you handle?

Key Takeaway
If you want to crack Accenture / Deloitte / PwC / TCS Analytics roles: Focus on DAX + SQL Windows + Python automation.

💬 Also, if you’re reading this…
 please comment “INTERVIEW” and share your experience too — it will help many job seekers ❤️
#powerbi #sql #python #accenture #dataanalytics #interviewexperience #businessintelligence #dax #interviewpreparation #dataanalyst

PEOPLE THINK I'M JUST POSTING ON LINKEDIN, BUT HERE'S WHAT THEY DON'T SEE.

Standing at Baga Beach, Goa, feet in the sand, watching the waves on my holiday.

My college friend texts: "Bro, how do you even make money?"

Fair question.

When people see me posting, they think it's just casual content.

But here's the reality behind those posts:

I've built a community of 19K+ data professionals who read my content every week.

I've positioned myself as the go-to person for Data Science and analytics advice.

I help data professionals grow in their careers - real guidance, no fluff, just actual results.

The best part? Everything I learn and experience becomes valuable content that helps others succeed.

The difference between my old life and now?

I can do all of this from a beach in Goa while on holiday.

Remember when "holiday" meant completely switching off your laptop?

Now as a data professional, I work from anywhere - laptop open, sea breeze, total freedom.

This didn't happen overnight. It took years of consistent work, building trust, and genuinely helping people.

But today, I have the freedom to work and live on my own terms.

What does your ideal work-life balance look like? Are you building towards that freedom?


The difference between my old life and now?

I can do all of this from a beach in Goa while on holiday.

P.S. Remember when "holiday" meant switching off your laptop completely? Now as a data professional, I work from anywhere—laptop open, sea breeze, total freedom. 🏖️💻

#linkedin #dataanalytics #career #growth #linkedincreators #life #dataanalyst

Everyone is learning data. But very few feel confident applying it.

Let’s be honest.

I’ve worked as a data analyst for years and mentored many students and professionals.

And I hear this all the time:
 “I know SQL.”
 “I practice Excel.”
 “I’m learning Power BI & Python.”

Yet the same fear remains: Is the job market too tough? Am I learning the right things? Am I even ready? 

Here’s the truth I always share:
👉 It’s not about knowing more tools.
👉 It’s about understanding how data solves real problems.

Stop chasing tools. Start thinking in data.

That’s why I say: 𝐌𝐚𝐬𝐭𝐞𝐫 𝐭𝐡𝐞 𝐝𝐚𝐭𝐚. 𝐓𝐡𝐞 𝐫𝐨𝐥𝐞 𝐰𝐢𝐥𝐥 𝐟𝐨𝐥𝐥𝐨𝐰.

If you’re feeling stuck or overwhelmed, I explain data in a simple, practical way. (Link in comments 👇)

#DataAnalytics #CareerInData #LearningData #YourMentor #LinkedIn #Youtube

In 2020, I was also confused.
 I used to think:

Stop watching random SQL/Python/Power BI videos…
If you’ve watched 50+ tutorials and still feel:
 ❌ confused
 ❌ stuck
 ❌ not job-ready
 ❌ no portfolio
 ❌ no interview confidence

Then listen carefully 👇
You don’t need more videos.
 You need a roadmap + projects + job strategy.
So I created something powerful:
🎥 The Only Data Analyst Roadmap You'll Ever Need (Job Guaranteed Method)
 ✅ 6-month plan
 ✅ real projects every month
 ✅ portfolio + resume + LinkedIn setup
 ✅ interview prep + job hunt routine
If you’re serious about becoming a Data Analyst in 2026, this will save you months of confusion.

📌 This roadmap gives you clarity + direction in 2026.

👉 Watch the full video here: [https://lnkd.in/d9eBGPUR]
💬 Comment “ROADMAP” and I’ll share the Road map pdf with you.

#DataAnalytics #SQL #PowerBI #Python #Portfolio

If you do this in interviews, you’ll lose the job.
I’ve seen this happen again and again.

A candidate has strong skills:
 ✅ SQL
 ✅ Power BI
 ✅ Analytics mindset
 ✅ Projects
But still… they don’t get selected.
Not because they lack knowledge.

 Because of one interview mistake 👇
❌ They start answering without understanding the question.
They hear the question and immediately begin talking…
➡️ “Yes I did this in my last project…”
 ➡️ “I used SQL window functions…”
 ➡️ “I made dashboards in Power BI…”
But they never confirm what the interviewer is actually asking.
And the result?
The answer becomes:
irrelevant
confusing
too long
not aligned with business need
Interviewers don’t reject you because you don’t know things.

 They reject you because they don’t trust your clarity.
✅ What to do instead (winning approach)
Before answering, take 3 seconds and do this:
1) Repeat the question in your own words
Example:
 “So you want to know how I handled missing values in the dataset, right?”
2) Ask 1 clarifying question
Example:
 “Are we talking about missing values in numerical columns or categorical too?”
3) Answer in structured format
Use this template:
 ✅ Context → ✅ Action → ✅ Result
 (or STAR method)


for follow for more Mukesh Sablani

𝐀𝐈 𝐃𝐢𝐝𝐧'𝐭 𝐑𝐞𝐩𝐥𝐚𝐜𝐞 𝐌𝐞 𝐚𝐬 𝐚 𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐬𝐭. 𝐈𝐭 𝐌𝐚𝐝𝐞 𝐌𝐞 𝟏𝟎𝐱 𝐌𝐨𝐫𝐞 𝐕𝐚𝐥𝐮𝐚𝐛𝐥𝐞. 𝐇𝐞𝐫𝐞'𝐬 𝐇𝐨𝐰.

AI did not replace me as a Data analyst. It made me 10x more valuable.

And last week proved it.

Our Operation team used to spend hours on file handling. Hundreds of CSV files. Manual transfers.

Manual merges. Pure grind. Sometimes a full day just moving data around.

Last week I built an automation using Python with the help of AI.

It transferred 400+ files and merged all CSVs cleanly. Total runtime was 3 -5 minutes.

That same work used to take hours.

Here is what changed after that:

My manager stopped checking my output because the system was reliable.
My team stopped wasting time on manual work and saved hours every week.
We spent that time on analysis and planning instead of busy work.

 I stopped doing repetitive tasks. I started managing workflows. I started reviewing logic instead of rows.

I started helping my team automate their tasks too.

This is the real shift. AI did the execution. I owned the system.

Here is how I work now:
I let AI draft Python scripts fast.
I review every function and edge case.
I focus on reliability and scale.
I free up time for my manager and my team.
I think about impact, not effort.

My workload went down. My team moved faster. My value went up.

If you are a data analyst, pay attention. The job is not disappearing.

The floor is rising. Those who learn to use AI will lead. Those who resist will struggle.

Have you used AI to automate your work? Share your experience below.

#dataanalytics #automation #AI #careergrowth #pythonprogramming

for follow more useful content Mukesh Sablani

𝐘𝐨𝐮𝐫 𝐁𝐨𝐬𝐬 𝐃𝐨𝐞𝐬𝐧'𝐭 𝐖𝐚𝐧𝐭 𝐃𝐚𝐭𝐚. 𝐓𝐡𝐞𝐲 𝐖𝐚𝐧𝐭 𝐓𝐇𝐈𝐒.
I've worked with data teams across multiple industries.
Not once did leadership ask for more dashboards.
They demanded 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀 𝘁𝗵𝗮𝘁 𝗺𝗼𝘃𝗲 𝗻𝘂𝗺𝗯𝗲𝗿𝘀.

After countless stakeholder meetings, 3 patterns became impossible to ignore 👇
1️⃣ 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝘁𝗵𝗮𝘁 𝗱𝗿𝗶𝘃𝗲 𝗮𝗰𝘁𝗶𝗼𝗻 𝘄𝗶𝗻 𝘁𝗿𝘂𝘀𝘁 𝗳𝗮𝘀𝘁
This wasn't about building perfect reports.
Leaders cared about:
the "so what?" behind every metric
recommendations with clear next steps
context that connects data to business goals
confidence in your analysis approach
If your insight doesn't change behavior, it's just noise.

2️⃣ 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝘀𝘂𝗽𝗽𝗼𝗿𝘁 𝘁𝗲𝘀𝘁𝘀 𝘆𝗼𝘂𝗿 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗮𝗰𝘂𝗺𝗲𝗻, 𝗻𝗼𝘁 𝘆𝗼𝘂𝗿 𝘁𝗼𝗼𝗹𝘀
No one asked me to create more visualizations.
They asked:
which option saves money or grows revenue
what happens if we do nothing
how confident are we in this path forward
what risks exist and how do we address them
Tools are table stakes. Business judgment separates you.

3️⃣ 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗶𝗺𝗽𝗮𝗰𝘁 𝗶𝘀 𝘆𝗼𝘂𝗿 𝗰𝘂𝗿𝗿𝗲𝗻𝗰𝘆 — 𝗲𝘃𝗲𝗻 𝗲𝗮𝗿𝗹𝘆 𝗶𝗻 𝘆𝗼𝘂𝗿 𝗰𝗮𝗿𝗲𝗲𝗿
Especially when budgets get tight.
You need to:
quantify the value of your work in outcomes
tie analysis to company priorities
track whether recommendations were implemented
show measurable before/after results

If you can't explain impact, you won't get buy-in.

Everyone's jumping into data these days. New courses, certificates, bootcamps everywhere.

But here's what I keep hearing: "I've done the courses... so why don't I feel ready for real jobs?"

After years in analytics and helping people break in, I've noticed something. Most people learn about data. They don't spend enough time actually using it to solve real business problems.

There's a big difference between:
👉 Knowing what metrics mean vs. explaining what they mean for this business.
👉 Building a dashboard vs. telling someone what to do because of it and honestly? Skills alone aren't enough.

The analysts I see doing well have something more:
👉 Curiosity that makes them ask "why?" again and again.
👉 Ownership that keeps them looking when the first answer doesn't make sense.
👉 Confidence to say "Here's what I found, and here's what we should do"

Your technical skills get you in the door. How you think and communicate keeps you growing.

So yes, learn the skills. But also think like someone who needs to make decisions with data. Act like someone the business can trust.

💬 For those learning data right now — what's your biggest challenge? I'd love to hear what you're facing.

#DataAnalytics #CareerInData #LearningData

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Mukesh Sablani

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The Battle

Sidharth Kriplani

Mukesh Sablani

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);}Mukesh Sablani's LinkedIn Performance

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