TrendyTech

Trendytech was founded out of my passion for Big Data technologies. 

We offer industry-oriented Big Data Hadoop & Spark Training to the working professionals as well as freshers:
Big Data Classroom Training
Big Data Corporate Training
Big Data Online Training
Big Data College Workshops

CEO & Founder of Trendytech

VMware

As a Big Data Cloud Engineer, I led the efforts towards design & implementation of VMC on AWS Analytics, Health, Monitoring and Alerting.

Technologies worked on: 
Java, Scala, Python, Apache Spark, Hive, Hbase, Mode Analytics, ELK stack, Amazon EMR

Product Link: https://cloud.vmware.com/vmc-aws

Member of Technical Staff, VMware

Cisco

Involved in Developing & Designing Big Data Systems to crunch large volumes of sales data and get insights which can drive decision making.

Led the Anaplan Data integration efforts from India.

Technologies worked on:
Java, Oracle, Sql, Linux, Informatica, Hadoop, Apache Spark, Hbase, ElasticSearch, Kibana, Anaplan Data modelling.

Big Data Developer, Cisco

Founder & CEO of Trendytech, offering high-quality Big Data Hadoop & Spark Training.

An alumnus of NIT Trichy and BITS Pilani, I am an expert Big Data trainer. I began my professional journey working for dream companies like Cisco & VMware. At Cisco, I was primarily involved in Developing & Designing Big Data Systems to crunch huge volumes of sales data and get insights which can drive business decision making. At VMware, I worked as a Big Data Cloud Engineer and led the effort to design and implement VMware on AWS Analytics, Health, Monitoring and Alerting.

Even while working my job, I had a passion to teach. That’s when I decided to quit my job and chase my passion: I now offer quality Big Data Training courses. 

To date, I have successfully trained 5000+ working professionals and students in Big Data. My unique & high standards of training quality have brought me 5-star ratings consistently.

My achievements include:
Won several connected recognitions majorly for my work on Big Data.
Winner of innovation Expo in Cisco for the project Customer Case Insights (San Jose)
Secured All India 4th Rank in NIMCET Exam jointly conducted by NIT’s
First runner-up in crazy programming, Pragyan NIT Trichy 2016.
Our Innovative idea of Distributed Resource Reservoir is being pursued as part of XLabs. 
Conducted many AICTE sponsored Big Data events with excellent reviews.

Contact me for Big Data Online Training


Here Comes the Gold mine for Data Engineers

Python Complete Playlist (5 videos already released)
lecture 1 - https://lnkd.in/gh_gVsTm
lecture 2 - https://lnkd.in/gCxba2zB
lecture 3 - https://lnkd.in/g6DVh4va
lecture 4 - https://lnkd.in/gs9TFEWK
lecture 5 - https://lnkd.in/gFPaaAM6

Free SQL Complete Course (one shot video 9 hours)
https://lnkd.in/gXTvqk3i

Data Engineering Mock Interviews (Data Engineers Club)
Interview 1 - https://lnkd.in/gjascwBm
Interview 2 - https://lnkd.in/g7AB8TNt
Interview 3 - https://lnkd.in/gzZBRcKu
Interview 4 - https://lnkd.in/gx9kg95h
Interview 5 - https://lnkd.in/gQ9kVUrf
Interview 6 - https://lnkd.in/gbxkjudi
Interview 7 - https://lnkd.in/g9e_Kiks
Interview 8 - https://lnkd.in/gshc46Pq
Interview 9 - https://lnkd.in/gfpNwNZK
Interview 10 - https://lnkd.in/gpchPS32

Everyday we are releasing one mock interview at 7 pm on my youtube channel.

Also more videos will be coming in the python playlist.

Do subscribe to my channel so that you do not miss out on anything.

Link to the channel - https://lnkd.in/gun_wZeK

Also, just to let you know that my new big data batch is starting tomorrow. To check more about my big data program you can visit https://lnkd.in/gZp_nBNR

Happy Learning!

#bigdata #dataengineering #interview #apachespark #sql #python

Sumit Mittal

Here Comes the Gold mine for Data Engineers - A complete Pack (Free)

Complete SQL Free Course - https://lnkd.in/gXTvqk3i

Complete Python Free Course (6 videos already released till now)
lecture 1 - https://lnkd.in/gsvRQyXq
lecture 2 - https://lnkd.in/g6Qwrkem
lecture 3 - https://lnkd.in/gyu_RcyM
lecture 4 - https://lnkd.in/gp5Z744p
lecture 5 - https://lnkd.in/gWdrtwsQ
lecture 6 - https://lnkd.in/gN2vPyGY

4 more videos to come in this python playlist

Data Engineering Mock Interviews (Pyspark, SQL, DSA, Data Modeling, System Design, Azure Cloud, AWS cloud)
Interview 1 - https://lnkd.in/gjascwBm
Interview 2 - https://lnkd.in/g7AB8TNt
Interview 3 - https://lnkd.in/gzZBRcKu
Interview 4 - https://lnkd.in/gx9kg95h
Interview 5 - https://lnkd.in/gQ9kVUrf
Interview 6 - https://lnkd.in/gbxkjudi
Interview 7 - https://lnkd.in/g9e_Kiks
Interview 8 - https://lnkd.in/gshc46Pq
Interview 9 - https://lnkd.in/gfpNwNZK
Interview 10 - https://lnkd.in/gpchPS32
Interview 11 - https://lnkd.in/gvhWJbDT
Interview 12 - https://lnkd.in/gtQGZyVc
Interview 13 - https://lnkd.in/gn6RSYTY
Interview 14 - https://lnkd.in/gpk35HRV
Interview 15 - https://lnkd.in/gXGVeUsg
Interview 16 - https://lnkd.in/gKBF6BVM
Interview 17 - https://lnkd.in/gGiDvPdF
Interview 18 - https://lnkd.in/gJTDWGJD
Interview 19 - https://lnkd.in/gS5-Kana
Interview 20 - https://lnkd.in/gHP9VeNN
Interview 21 - https://lnkd.in/g_n-Ku58
Interview 22 - https://lnkd.in/guTJg2Gi
Interview 23 - https://lnkd.in/gHSgC5Mi
Interview 24 - https://lnkd.in/gdDPJE4M

Do subscribe to my channel so that you do not miss out on anything.

Link to the channel - https://lnkd.in/gun_wZeK

Also, just to let you know that my new big data batch is starting next Saturday. To check more about my big data program you can visit https://lnkd.in/gP4HjwmQ

Happy Learning!

#bigdata #dataengineering #interview #apachespark #sql #python

I am looking to hire 2 people for developing innovative solutions around Big Data technologies.

Initially I will provide a paid internship and then if things go well, 
I will convert it to a full time role.

My preferred choice for this hiring will be 
- Candidates with a career Gap (currently on a break)
- Freshers

The candidates should have some idea on big data technologies.
Some knowledge on web development will be a great add on.

If interested you can DM me on linkedIn or mail me your resume on sumit@trendytech.in

If you are already working somewhere, then this position is not for you.

#bigdata #hiring #dataengineering

𝗠𝘆 𝗷𝗼𝘂𝗿𝗻𝗲𝘆 𝗶𝗻 𝘁𝗵𝗲 𝗱𝗮𝘁𝗮 𝗳𝗶𝗲𝗹𝗱 𝗯𝗲𝗴𝗮𝗻 𝗯𝗮𝗰𝗸 𝗶𝗻 𝟮𝟬𝟭𝟰 𝘄𝗵𝗲𝗻 𝗜 𝗷𝗼𝗶𝗻𝗲𝗱 𝗧𝗖𝗦 𝗮𝗻𝗱 𝗿𝗲𝗮𝗹𝗶𝘇𝗲𝗱 𝘁𝗵𝗲 𝘀𝗶𝗴𝗻𝗶𝗳𝗶𝗰𝗮𝗻𝗰𝗲 𝗼𝗳 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗮𝗻𝗱 𝗱𝗮𝘁𝗮 𝘄𝗮𝗿𝗲𝗵𝗼𝘂𝘀𝗶𝗻𝗴

In the wake of the pandemic, with data exploding, I recognized the need to Upskill and propel my career in data engineering. 

I started watching youtube videos & other stuff and I found myself stagnating in my progress. 

That's when I made the decision to invest in Sumit Mittal's program.

Sumit Sir's focused approach solely on data engineering, coupled with his unique teaching style and clear course structure, proved to be immensely beneficial.

I successfully cracked 6 interviews for data engineering roles.

And recently joined at Tiger Analytics as a Data Engineer with over 100% hike.

If anyone is serious about advancing career in big data, I highly encourage you to consider joining Sumit sir's TrendyTech course.

#dataengineer #sumitmittal #trendytech #tigeranalytics #upskill

These 30 videos will help you for your next Data Engineering Interview! 

1. Explaining Data Lake Versus Data Warehouse - https://lnkd.in/gn6_UFtE

2. Learn Columnar Storage - 
https://lnkd.in/gcH5XAsZ

3. Analysing the failed Spark Jobs using Log Files - https://lnkd.in/gvFs_vve

4. Understanding Apache Spark Repartition and Coalesce - 
https://lnkd.in/gxwpwaJi

5. Understanding the Different Kinds of Triggers in Azure Data Factory -
https://lnkd.in/g9iyV8XB

6. Spark Execution Plan - 
https://lnkd.in/g36UQ3sq

7. RDDs Vs DataFrames - 
https://lnkd.in/gMnyxRq4

8. Apache Spark Optimization techniques -
https://lnkd.in/gBsch9gZ

9. Exploring Spark's withColumn() Method for Powerful-
https://lnkd.in/gaAvdeyM

10. Understanding Parallel Processing in Apache Spark - 
https://lnkd.in/gTAtuphb

11. Understanding Lineage Graph and Lazy Evaluation in Apache Spark - 
https://lnkd.in/gRYGsGWK

12. Understanding an Important Optimization Technique in Apache Spark - 
https://lnkd.in/gjVbtSSR

13. Understanding Narrow Vs Wide Transformations in Apache Spark -
https://lnkd.in/g3UY85_t

14. Understanding DAG Vs Lineage Graph in Apache Spark - 
https://lnkd.in/ganUX--C

15. Control Vs Data Flow in Azure Data Factory  - 
https://lnkd.in/gr5Xgjs3

16. Understanding Jobs, Stages, Tasks and Partitions in Apache Spark -
https://lnkd.in/gaiUmhHu

17. Exploring Lazy Evaluation in Apache Spark -
https://lnkd.in/ggJJjirR

18. Understanding Dataframe Write Modes in Spark - 
https://lnkd.in/gJq7v3yJ

19. Databricks Vs Spark Vanilla Version - 
https://lnkd.in/gNWEzHjW

20. Learning to Determine the Number of Executors and Executor Memory - 
https://lnkd.in/gaqZQP5y

21. Exploring the Best Approach for Schema Management - 
https://lnkd.in/gCzQysQz

22. Understanding how to Handle Incremental Data without Primary Key - 
https://lnkd.in/g-BjsdK8

23. Cluster Configuration in Apache Spark - 
https://lnkd.in/gw9Jfk9r

24. CAP Theorem -
https://lnkd.in/g-nxt6yU

25. Understanding the Different Join Strategies in PySpark - 
https://lnkd.in/gRDNQjw4

26. Partitioning Vs Bucketing -
https://lnkd.in/gXaxnduK

27. Understanding how to Optimize PySpark Job - 
https://lnkd.in/gS7u2vQh

28. Understanding SCD - 
https://lnkd.in/gwxhUvSx

29. Ensuring Data Quality in  Spark -
https://lnkd.in/g3h3wrSk

30. Partitions and CPU Core Allocation in  Spark - 
https://lnkd.in/gCaiu4w6

Save it for future reference!

#bigdata #dataengineering #interviews

Data Engineers Interview Preparation - A complete Package (Free)

Complete SQL Free Course - https://lnkd.in/ghR66QR5

Complete Python Free Course (6 videos already released till now)

lecture 1 - https://lnkd.in/gMJxn-CE
lecture 2 - https://lnkd.in/gjuHD7KE
lecture 3 - https://lnkd.in/gAjJT-hJ
lecture 4 - https://lnkd.in/gmCd4aP7
lecture 5 - https://lnkd.in/gWn8sFmb
lecture 6 - https://lnkd.in/gE72eRCM

more videos in python playlist yet to come..

Data Engineering Mock Interviews (Pyspark, SQL, DSA, Data Modeling, System Design, Azure Cloud, AWS cloud)

Interview 1 - https://lnkd.in/gqqFZWTU
Interview 2 - https://lnkd.in/gPQYVMec
Interview 3 - https://lnkd.in/g3u5Ny2E
Interview 4 - https://lnkd.in/gxBdxpVV
Interview 5 - https://lnkd.in/gWsh2RWd
Interview 6 - https://lnkd.in/gnGvpZyt
Interview 7 - https://lnkd.in/g6hgFjRk
Interview 8 - https://lnkd.in/gUWfa9X6
Interview 9 - https://lnkd.in/gb6ycMJp
Interview 10 - https://lnkd.in/gf-ECG4F
Interview 11 - https://lnkd.in/gyeYd58X
Interview 12 - https://lnkd.in/gucQaRff
Interview 13 - https://lnkd.in/grQVGw9T
Interview 14 - https://lnkd.in/gq8uwXi9
Interview 15 - https://lnkd.in/gqeMxyUm
Interview 16 - https://lnkd.in/gVNTAwtU
Interview 17 - https://lnkd.in/gR9F3g9f
Interview 18 - https://lnkd.in/gQpwDf_r
Interview 19 - https://lnkd.in/gPZWJ9Vd
Interview 20 - https://lnkd.in/gFGreuSn
Interview 21 - https://lnkd.in/ggJqR5ai
Interview 22 - https://lnkd.in/gkEp2rr8
Interview 23 - https://lnkd.in/gMi8zvs4
Interview 24 - https://lnkd.in/gr9B6RXP
Interview 25 - https://lnkd.in/gYvxhTgj
Interview 26 - https://lnkd.in/g364Tt3D
Interview 27 - https://lnkd.in/gmWgfWeZ
Interview 28 - https://lnkd.in/g8Yi7hgX
Interview 29 - https://lnkd.in/ghEbHznY

Do subscribe to my channel so that you do not miss out on anything.

Link to the channel - https://lnkd.in/gRXA_cvv

To check about my big data program you can visit https://lnkd.in/gWBA7p4D

Happy Learning!

#bigdata #dataengineering #interview #apachespark #sql #python

CICD for Data Engineers in a Super Easy way!

Lets say you are working on a RetailAnalysis Project & have a Jira ticket assigned to you RA-17843 

If you are a developer you would create a feature branch,
feature-RA-17843 & work on it.

As soon as you make a git push, and github receives the new code a pipeline should run which involves:

Build - creating a virtual environment & install all the dependencies (In case of python)

Test - Run unit test cases / Quality checks

Package - Create a package, can be a zip of code

Deploy - Send the code bundle to edge node using SCP

If we do all of these manually it will be very time consuming and error prone. 

So all of the above steps should run as a automated pipeline step by step.

We can automate it using a automation server such as Jenkins.

So anytime a new branch is created, or a git push happens all of the build -> test -> package -> deploy should run without any manual involvement.

Now Let us understand the branching structure based on different environments which most of the data engineering projects follow.

Feature branches -> Dev -> Test -> UAT -> main (Prod)

Note - In a few companies its just Dev & Prod, so it depends.

Feature branch - where developers codes their new changes.
Dev - Development branch
Test - For QA team to test 
UAT - for user acceptance testing
main - this is the production branch

Feature branches are short lived that means once feature branch is merge to a higher branch we can delete it.

All the other branches will be there always.

so when we make a code push to feature branch in github then all the 4 steps in CICD pipeline will run.

If we see all the 4 steps ran fine, then we can raise a pull request to merge our code to Dev branch. once the reviewers see and merges it, the automated pipeline should run again on Dev branch.

Same way when code is merged to Test, UAT & main the pipeline should run.

Most of the companies follow the similar structure for CICD in data engineering projects.

As a data engineer you should not go too deep into it, but you should have a fair idea. Ideally the entire process would be set, you would have to just follow that.

Do mention in comments on what CICD process you follow in your company!

I hope you would have liked the post, I tried my best to explain in simple words.

I have covered all of this in great detail in my ultimate data engineering program. To know more about my program visit my website https://lnkd.in/gZp_nBNR

It's a life changing program!

#dataengineering #bigdata #apachespark #cicd #devops

This repository for Data Professionals is getting bigger and better each day!

Three Key updates -
- 3 more mock Interviews & 1 python video added since the last time
- Just released a video on "Mastering Dictionary Data Structure in Python"
- Satinder Singh took a interview, and it has been the talking point, do watch!

Python Complete Playlist (5 videos released till now)
lecture 1 - https://lnkd.in/gh_gVsTm
lecture 2 - https://lnkd.in/gCxba2zB
lecture 3 - https://lnkd.in/g6DVh4va
lecture 4 - https://lnkd.in/gs9TFEWK
lecture 5 - https://lnkd.in/gFPaaAM6

Free SQL Complete Course (one shot video 9 hours)
https://lnkd.in/gXTvqk3i

Data Engineering Mock Interviews (Data Engineers Club)
Interview 1 - https://lnkd.in/gjascwBm
Interview 2 - https://lnkd.in/g7AB8TNt
Interview 3 - https://lnkd.in/gzZBRcKu
Interview 4 - https://lnkd.in/gx9kg95h
Interview 5 - https://lnkd.in/gQ9kVUrf
Interview 6 - https://lnkd.in/gbxkjudi
Interview 7 - https://lnkd.in/g9e_Kiks
Interview 8 - https://lnkd.in/gshc46Pq

Everyday we are releasing one mock interview at 7 pm on my youtube channel.

Also more videos will be coming in the python playlist.

Do subscribe to my channel so that you do not miss out on anything.

Link to the channel - https://lnkd.in/gun_wZeK

Enjoy the series!

For those who do not know me, I teach big data. you can get more details about my big data course on my website https://lnkd.in/gZp_nBNR

#bigdata #dataengineering #interview #apachespark #sql #python

𝐖𝐞𝐛 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫 𝐢𝐧 𝐓𝐂𝐓𝐒 𝐭𝐨 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 𝐢𝐧 𝐇𝐒𝐁𝐂 

250% hike in a dream job is just impossible.

After Masters degree in CS ,2 years gone in Non Technical job and 2 years in DotNet.

Starting I worked as a Dot Developer but due to the company's process revamp I was moved to the non tech department.

Life looks boring & difficult to live in this job

Transition was the need as oxygen & I selected Data line for me.

I tried various courses but they lacked clarity ,have complex examples and after some point I loose motivation

I failed in 15+ interviews but not stopped

Sumit Mittal Sir's Big Data courses info on Youtube attracts my attention .

This course was costly but very clear & looks perfect.

I managed for 2 months & enrolled for this course.

Sumit Mittal Sir upskilled me & also guided me in my career transitioning.

Saturday Classes by Sumit Sir are boster dose for motivation & guidance.

After in depth knowledge & practice I cracked many offer .

And after 4 tough years , I joined HSBC as Data Enginner with 250% hike.

Thanks Sumit Mittal Sir & TrendyTech for this Life changing program.

If you are looking for career transition please be patient, good things takes time.

Even if you are from Non Tech role or Fresher just get started ,you'll succeed in your goals definitely.

#success #hsbc #trendytech #bigdataengineer #sumitteachings

what is meant by Data Modeling?

A way to structure your data so that it fits your needs in the best possible way.

Needs can be different based on what system are we Modeling & who is the end user?

model the table in a way that reduces the storage space, 
modeling it in a way that queries run faster, 
modeling in a way that user can easily query
etc..

In a transactional system (OLTP) we generally use Normalization -
It's a technique to divide one big table into multiple smaller tables with an intent to reduce the redundancy.

However, OLTP systems are not meant to do reporting?
our reporting work can overload the OLTP systems

Datawarehouse (DWH) is best fit for reporting purpose (OLAP)

What is DWH - it's like a Database but the objective is to make your analytical queries faster.

Dimensional Modeling is one of the well know techniques for modeling a DWH.

here are 2 definitions that you should know - 

- "Dimensional Modeling is a design technique for Databases intended to support end user queries in a DWH"
Ralph Kimball

 - the process of modeling a business process into a series of facts and dimension tables designed for analysis.

Key highlights of a Transactional DB design
- designed towards fast maintenance of data
- inserting and updating is quick
- very small sets of data is retrieved in a query
- Data consistency is critical
- Focus is on customers who are entering the data

Reporting DB design
- copy of transactional data (not exactly the same way)
- the resulting model reflects the kind of questions business wants to ask rather than the functions of underlying operational system.
- Descriptive data like customer name, customer address is separated from the quantity data such as order quantity, order amount.
- larger datsets
- insert and update speed is not relevant
- performance focus is on retrieving the data quickly.

fun facts regarding facts & dimension tables
=> dimension tables would contain more than 90% of total columns, however data in fact table would be more as we keep getting new data.
=> in fact table the foreign keys might take more space then the actual fact information .

When storage was costly, Dimension modeling ruled and it's even ruling today.

Now a days OBT (one big table) is also becoming popular, because storage space is not a big concern. We can pay little extra for storage if that helps us to build faster queries, and it's easy for end users to query it.

will OBT take a lead over Dimensional modeling in the future?

#bigdata #datawarehouse #datamodeling #dataengineering #database 

I am working as a Data Engineer since 2022 but there was some gaps in big data concepts. 

I tried to learn Big Data via various courses, but still I was not confident enough.

After some research, I found Sumit Mittal  Sir course at TrendyTech 


But it looks costly and then I thought lets do this investment once & lets see the returns.

I selected this course because of -

1. Clear structure of course - All dots connected properly
2. Teaching Style - Best teacher ever seen
3. Simplifying the complex concepts ,so that it looms very easy to understand.
4. Practical knowledge 

Sumit Mittal Sir’s goes into so much depth of the topic and explains it in a very simple way that anyone can understand it easily and you don't have to revise it again and again.

In short time I was able to master the concepts of Big Data & Cloud.

I cracked multiple interviews and finally I have joined Thoughtworks as a Data Engineer.

Coincidentally, Walmart's Ex SDE and Ex Senior SDE took my technical interview. 

I want to thank Sumit Sir for his intensive efforts in creating this course.

Lets upskill properly because this quality will remain with you forever & also returns will come for whole life.

#Success #thoughtworks #trendytech #bigdataengineer #sumitteachings

𝗧𝗿𝗮𝗻𝘀𝗶𝘁𝗶𝗼𝗻 𝗳𝗿𝗼𝗺 𝗕𝗧𝗲𝗰𝗵 𝗘𝗹𝗲𝗰𝘁𝗿𝗶𝗰𝗮𝗹 𝘁𝗼 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝗶𝘀 𝘄𝗼𝗿𝘁𝗵 𝗶𝘁.

Airflow, PySpark & Spark with Scala were the key for me to crack Data Engineering interviews.

My Senior achieved success & guided me to take a step in taking Sumit Sir Ultimate Big Data Program.

Heartfelt gratitude to Mphasis, ANZ and Sumit Sir for sculpting me into a proficient Data Engineer.

Sumit Mittal  Sir’s teaching style is unique & complete course is by him only.

Learning from him was both captivating and effortless; the robust foundation laid by the course made complexities appear simple

With my full-time job, I used to learn 2-3 hours daily.

But meanwhile I met with an accident and had to get operated.It was a tough time for me had to take a pause but still managed to give at least 30 minutes a day.

I completed 70% course only  but started getting interview calls.

Cracked many interviews & joined ANZ as Data Engineer.

Thanks Sumit Mittal  Sir for helping me in becoming a perfect Data Engineer.

#success #trendytech #anz #bigdataengineer #sumitteachings

A journey from 0 Subscribers to a Silver Play button

Thank you all for supporting me always.

Feeling Grateful!

#thankyouall

Even if you have done a few python paid courses, check these 6 videos that I have uploaded on youtube.

You will truly realize that you didn't knew things this way & in this depth.

1. https://lnkd.in/gsvRQyXq

2. https://lnkd.in/gUK_fvvy

3. https://lnkd.in/gZzeSY7y

4. https://lnkd.in/gyfj7ThV

5. https://lnkd.in/gFqMvgPX

6. https://lnkd.in/gcqh2cjE

In the above 6 videos I have covered all the 4 major data structures. List, Tuple, Dictionary & Set.

I have talked about the real time usecases rather than dummy examples.

To check on my big data courses visit my website https://lnkd.in/gP4HjwmQ

#bigdata #dataengineering #python

From a CTC of 12 LPA to 30+ LPA in 7 months 

Multiple offers & an extremely good hike, 
that's what a well planned learning can help you achieve.

It's such a joy to see your students getting tremendous success.

My advice to everyone out there, a few failures in life should not demotivate you.

A 7-8 months of rock solid, consistent effort can take your career to absolutely new heights.

So keep working hard, you will be amazed with the results.

PS~ I teach big data. visit my website https://lnkd.in/gkXgKRJx to know more about my big data program. The new batch is starting on coming Saturday.

#bigdata #dataengineering #success #career

23 SQL videos that will make you fall in love with SQL

SQL Basics (14 videos)

📌 SQL Fundamentals, CRUD Operations & Setting Environment - 
https://lnkd.in/ekBxGU2c

📌 Primary Key vs Unique Key, Auto Increment Values -
https://lnkd.in/eXSugBVX

📌 DDL vs DML, Truncate vs Delete -
https://lnkd.in/eCEj6NHc

📌 Foreign Key Constraint -
https://lnkd.in/ebfYyM2b

📌 Distinct, Order By, Limit, Like Keyword -
https://lnkd.in/ec-McKnC

📌 Order of execution in SQL -
https://lnkd.in/eShPzDCJ

📌 Aggregate Functions in SQL -
https://lnkd.in/e2HQQZj3

📌 Datatypes in SQL -
https://lnkd.in/eJ7prXMR

📌 Logical Operators in SQL -
https://lnkd.in/eubjUHeD

📌 Joins in SQL - 
https://lnkd.in/e63jvjec

📌 Difference between where and having in mysql -
https://lnkd.in/eTwb9pcJ

📌 Over Clause & Partition By Clause -
https://lnkd.in/ewspqCVS

📌 Row Number Function in MySQL -
https://lnkd.in/eK9-Ef4P

📌 Rank & Dense Rank -
https://lnkd.in/en83Pr5V

SQL Advanced (2 videos)

📌 CTE in SQL -
https://lnkd.in/e-cKsd89

📌 SQL internals -
https://lnkd.in/erwxZY8J

SQL Leetcode (8 problems)

📌 LeetCode 175 - combine 2 tables
https://lnkd.in/eMmX8DQa

📌 Leetcode 176 - Second highest salary (3 approaches)
https://lnkd.in/eaDRxzSd

📌 Leetcode 178,180,181 - Rank Scores, Consecutive Numbers, Employees Earning More Than Their Managers
https://lnkd.in/efibXrXG

📌 Leetcode 182,183 - Duplicate Emails, Customers Who Never Order
https://lnkd.in/e9ZSr9s2

📌 LeetCode 184 - Department Highest Salary
https://lnkd.in/evpeZrJh

Link to subscribe to my youtube channel -
https://lnkd.in/geJt-sMS

happy learning!

#sql

I am excited to announce that I have recently joined HARMAN India as a Senior Data Engineer. 

My journey into the world of big data has been both challenging and rewarding. 

Initially, I found myself overwhelmed with the vast amount of information available on platforms like YouTube.

But the information is not structured and confused me even more.

In my quest to gain a deeper understanding of big data, I explored numerous courses and tutorials but struggled to find a good learning experience. 

Then I came across Sumit sir's Big Data Master Program, recommended by friends and backed by solid research.

Sumit Mittal's teaching style is truly remarkable, making complex concepts in big data not only understandable but also enjoyable. 

This course is well designed for Beginners to Advanced level.

Thanks to Sumit Sir's guidance and support, along with the assistance of Team TrendyTech, my family, and friends, I successfully navigated through multiple interviews and landed a role at Harman.

#dataengineering #bigdata #trendytech #sumitmittal

New Updates - The Data Engineers Club 

What we as a community achieved in last 3 weeks?

We managed to conduct more than 25 mock Interviews, and 14 of them have been uploaded on youtube for the audience to learn from them.

Data Engineering Mock Interviews uploaded on youtube
Interview 1 - https://lnkd.in/gjascwBm
Interview 2 - https://lnkd.in/g7AB8TNt
Interview 3 - https://lnkd.in/gzZBRcKu
Interview 4 - https://lnkd.in/gx9kg95h
Interview 5 - https://lnkd.in/gQ9kVUrf
Interview 6 - https://lnkd.in/gbxkjudi
Interview 7 - https://lnkd.in/g9e_Kiks
Interview 8 - https://lnkd.in/gshc46Pq
Interview 9 - https://lnkd.in/gfpNwNZK
Interview 10 - https://lnkd.in/gpchPS32
Interview 11 - https://lnkd.in/gvhWJbDT
Interview 12 - https://lnkd.in/gtQGZyVc
Interview 13 - https://lnkd.in/gn6RSYTY
Interview 14 - https://lnkd.in/gpk35HRV

what is planned?

we will be conducting more interviews on weekends, and in next 16 days you will see 16 more interviews coming up on youtube.

Also, The first In person meetup is planned in mid of May. It will be in Bangalore. 
However this will be a invite based event. we want to limit it to 120 participants max as we are doing it for the very first time.

Are you interested to be a part of this community and help others out?

If yes, then you can help under one of the below category

1. Conduct Mock Interviews - Do you take Interviews (Data Engineering) in your company, if yes then you can help me with taking mock interviews.

2. Attend Mock Interviews - You feel you are prepared for Giving Interviews, and want to attend a mock interview to see whats your prep level.

3. Share your Experiences - Are you are a Leader in Data Engineering field & have your experiences that you wish to share. example: challenges that you faced with implementations and how your team overcome that.

4. Share Interview Experiences - Have you attended multiple interviews and then cracked a few, you can help others by sharing your interview experiences.

If you are someone who really want to help me in this mission, 
then just DM me on linkedIn talking about in which category you want to help.

This will be a really good opportunity for you to help the Data Engineering community.

#bigdata #dataengineering #thebiggestcommunity

𝗟𝗼𝘃𝗲 𝘁𝗼 𝘀𝗶𝘁 𝗶𝗱𝗹𝗲 𝗶𝗻 𝘀𝗮𝗺𝗲 𝗰𝗼𝗺𝗽𝗮𝗻𝘆 & 𝘄𝗶𝘁𝗵 𝘀𝗮𝗺𝗲 𝗽𝗮𝗰𝗸𝗮𝗴𝗲 ?

IT jobs looks attractive but it is tough to grow here.

I was working as Software Analyist from last 4 years.

And how to Grow was not clear.

I tried to upskill and done few courses on YouTube but they are not properly structured.

I couldn't crack interviews & gets demotivated .

After lot of analysis joined Sumit Mittal Sir Ultimate Big Data Course.( Azure focused)

This course has clear structure & all by Sumit Mittal  Sir with unique teaching style.

I cracked many interviews & joined LTIMindtree  as Senior Data Engineer.

Happy with Growth & work here .

As per my experience Sumit sir teaching style will make the learning super easy.

All IT professions will agree that without continuous  uspskilling growth is not possible in IT sector.

#bigdataengineer #ltimindtree #trendytech #Success #sumitteachings

"The Elite Data Engineering Program" - New Launch

I am super excited to announce the launch of my new program

It's a 20 weeks program

High level topics covered in the Elite DE program are:

=>Distributed Storage & Processing Fundamentals
=>Pyspark in Depth
=>A lot of performance tuning techniques
=>An extensive project usecase on Pyspark
=>Apache Hive
=>Data Modeling & System Design
=>Structured streaming with Kafka along with a mini project
=>Important AWS cloud services with a mini project

Why this new program when I already have Ultimate Data Engineering Program?

A lot of people requested me asking, they wish to do something in around 20 weeks.

For those who do not know, my ultimate program is a 32 weeks extended program.

So Elite is a little shorter in terms of duration.

Now you might ask then whats the difference between, The Ultimate Program and the newly launched Elite Program?

Let me explain the difference.

AWS & Azure are the 2 major trending Cloud in Data Engineering.

These days, Knowing one cloud is a must, knowing multiple clouds is a good add on.

In Ultimate program I am covering both of these (Azure & AWS)

However in Elite I am covering AWS cloud.

The Ultimate Program (32 weeks) = Elite Program (20 weeks) + Azure Data Engineering (12 weeks)

So how to decide which program to opt for?

Elite Program will be best suited if you don't want to spend 32 weeks,
and feel 20 weeks is a good time to learn. Also you do not have a specific requirement to learn Azure.

Ultimate Program will be best suited when you do not have a time crunch, and you feel you can spend 32 weeks in your learning. Also when you feel you definitely have to learn important Azure services mainly Databricks & Datafactory.

I hope this would have given the clarity.

To know more about Elite program visit the below link:
https://lnkd.in/gZp_nBNR

New batch starting today!

#bigdata #dataengineering #apachespark #kafka #awscloud

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