📌𝐃𝐚𝐭𝐚 𝐒𝐭𝐨𝐫𝐲𝐭𝐞𝐥𝐥𝐢𝐧𝐠 𝐢𝐬 𝐚𝐧 𝐚𝐫𝐭!!

👉Create data visuals with compelling outcomes that conveys information more precisely.

❄️Sharing an amazing "𝐓𝐚𝐛𝐥𝐞𝐚𝐮 𝐆𝐮𝐢𝐝𝐞𝐛𝐨𝐨𝐤" 💥

Happy Learning !!!

Message me:- @stockkida

#datavisualization #data #tableau #technology #visualization #learning #dataanalytics #businessintelligence #linkedinforcreators

5 𝐟𝐫𝐞𝐞 𝐜𝐨𝐮𝐫𝐬𝐞𝐬 𝐭𝐡𝐚𝐭’𝐥𝐥 𝐡𝐞𝐥𝐩 𝐥𝐞𝐚𝐫𝐧 #javascript 10𝐱 𝐛𝐞𝐭𝐭𝐞𝐫 𝐭𝐡𝐚𝐧 𝐭𝐡𝐞 𝐏𝐚𝐢𝐝 𝐨𝐧𝐞𝐬🤩

𝑴𝒖𝒔𝒕 𝑺𝒂𝒗𝒆 𝒂𝒏𝒅 𝑺𝒉𝒂𝒓𝒆 !!!!


1) 𝐋𝐞𝐚𝐫𝐧 𝐉𝐚𝐯𝐚𝐒𝐜𝐫𝐢𝐩𝐭 𝐛𝐲 𝐒𝐜𝐫𝐢𝐦𝐛𝐚

👉 This is perhaps the most interactive JavaScript course ever recorded.
It contains 140+ coding challenges, meaning that you will finally build that ever-so-important JavaScript muscle memory.

🔗 https://lnkd.in/gkUvjJXC



2) 𝐉𝐚𝐯𝐚𝐒𝐜𝐫𝐢𝐩𝐭 𝐓𝐮𝐭𝐨𝐫𝐢𝐚𝐥 𝐟𝐨𝐫 𝐁𝐞𝐠𝐢𝐧𝐧𝐞𝐫𝐬 - 𝐅𝐮𝐥𝐥 𝐂𝐨𝐮𝐫𝐬𝐞 𝐢𝐧 12 𝐇𝐨𝐮𝐫𝐬 (2022)

👉 Best Free JavaScript Programming Course by Clever programmer

🔗 https://lnkd.in/gR-Ki4Uk



3) 𝐁𝐄𝐒𝐓 𝐉𝐚𝐯𝐚𝐒𝐜𝐫𝐢𝐩𝐭 𝐓𝐮𝐭𝐨𝐫𝐢𝐚𝐥 𝐟𝐨𝐫 𝐁𝐞𝐠𝐢𝐧𝐧𝐞𝐫𝐬 𝐟𝐨𝐫 𝐆𝐞𝐭𝐭𝐢𝐧𝐠 𝐚 𝐉𝐨𝐛 (𝐇𝐢𝐠𝐡 𝐐𝐮𝐚𝐥𝐢𝐭𝐲, 𝐏𝐫𝐨𝐣𝐞𝐜𝐭 𝐁𝐚𝐬𝐞𝐝 𝐂𝐨𝐮𝐫𝐬𝐞)

👉 Build a full app in this JavaScript tutorial, designed to help new programmers get into the tech industry. Exercises, code, cheatsheet.

🔗 https://lnkd.in/gVXqp2ZY



4) 𝐉𝐚𝐯𝐚𝐒𝐜𝐫𝐢𝐩𝐭 𝐅𝐮𝐥𝐥 𝐂𝐨𝐮𝐫𝐬𝐞 2022 𝐛𝐲 𝐒𝐢𝐦𝐩𝐥𝐢𝐥𝐞𝐚𝐫𝐧

👉 This javascript tutorial for beginners focuses and major fundamentals to help you secure the right skills, tips, and tricks to be industry-ready according to the current IT standards.

🔗 https://lnkd.in/gVnc9fvn


5) JavaScript Crash Course by Codevolution

👉 This course will teach JavaScript from the bottom to the top.
It’s a gem!

🔗 https://lnkd.in/gcPNGJGD

for more such content.

#learningeveryday #javascriptdeveloper #javascript #frontend #react #developer #programming #learning #softwareengineering #coding #tech #engineering #engineer

▲illustration of data processing from raw to end user▲

◾its step by step process how data flows from data source.

• data source: data source is simply the source of the data.

•data loaders: data loader is a application for the bulk import or export of data.

•data lake: a data lake is a centralized repository designed to store, process, and secure large amounts of structured, semi structured, and unstructured data.

• data visualization: data visualization is a way to represent information graphically, highlighting patterns and trends in data.

• ml development: machine learning deals with the issue of how to build computer programs that improve their performance at some tasks through experience.
graphic credit: semantix (data platform)
◾this infographics delivers highly valuable information to understand the flow of data.
tags-
#data #engineering #analytics #science #intelligence #visualization #machinelearning #bigdata #dataengineering #computing #datascience #dataanalytics #datamining #ai #ml #learning

One Diagram to Refer for Microservices Roadmap


Companies like Netflix, Amazon, and others have adopted the concept of microservices in their products due to large benefits offered by microservices.

As we understand, many developers want to know how they should start this journey. So I decided to make this journey clearer by defining a road map for this learning curve.

Container - A container is a standard unit of software that packages up code and all its dependencies so the application runs quickly and reliably from one computing environment to another.

Container orchestration automates containers' deployment, management, scaling, and networking. Enterprises that need to deploy and manage hundreds or thousands of Linux® containers and hosts can benefit from container orchestration.

Load balancer is a device that acts as a reverse proxy and distributes network or application traffic across several servers.
Load balancers are used to increase the capacity (concurrent users) and reliability of applications.

Monitoring and Alerting : In a microservice architecture, if you want to have a reliable application or service, you have to monitor the functionality, performance, communication, and any other aspect of your application in order to achieve a responsible application. Promethous is widely popular.

Distributed Tracking - when it comes to microservice architecture, a request may be passed through different services, which makes it difficult to debug and trace because the codebase is not in one place, so here distributed tracing tool can be helpful.

Message Broker - A message broker is software that facilitates the exchange of messages between applications, systems, and services.

Database - in most systems, we need to persist data, because we would need the data for further processes or reporting, etc.


Caching - Caching reduces latency in service-to-service communication of microservice architectures.

Cloud service provider -is a third-party company offering a cloud-based platform, infrastructure, application, or storage services.

API Management: API management is the process of designing, publishing, documenting, and analyzing APIs in a secure environment.

Application Gateway -An application gateway or application level gateway (ALG) is a firewall proxy that provides network security. It filters incoming node traffic to certain specifications, meaning only transmitted network application data is filtered.

Service Registration -A service registry is a database used to keep track of the available instances of each microservice in an application. The service registry needs to be updated each time a new service comes online and whenever a service is taken offline or becomes unavailable.



#microservices #microservicesarchitecture #database #nosql #architecture #systemdesign #java # #cloud #software #management #kubernetes #docker #deveops# #learning #learningeveryday

Why most people won't grow despite learning?

They read 100s of books, 100s of videos, & feel they have learnt

Many times attending 100s of seminars & workshop, some go for free & some paid

Come back charged up & wait for things to happen with little actions

Can you imagine nothing changes as they will attend these programs again ?

One thing that I learnt from my mentors is getting insight

Going a step further this is what model will you apply

Information + Insights + Application + Experience = Wisdom

When you achieve this wisdom that is when you grow

One of the learning model below
Learn + Apply + Practice

How many of you have aha moment?


#education #learning #personaldevelopement

Amazon || 𝐑𝐞𝐜𝐫𝐮𝐢𝐭𝐦𝐞𝐧𝐭 𝐏𝐫𝐨𝐜𝐞𝐬𝐬 𝐅𝐨𝐫 𝐒𝐃𝐄 1🤩 
 
𝑴𝒖𝒔𝒕 𝑺𝒂𝒗𝒆 𝒂𝒏𝒅 𝑺𝒉𝒂𝒓𝒆 !!!!
 
 
It's every engineer's dream to get into top product-based companies, some of us called them FAANG or MAANG. Here I am sharing the journey you will go through the interview process from Amazon.


𝐂𝐓𝐂 𝐁𝐫𝐞𝐚𝐤𝐝𝐨𝐰𝐧 (Source : Internet) :

Base Salary : 19LPA
Bonus : 6.5 LPA(Y1) + 5 LPA (Y2)
RSU : 15.5 LPA
Total Compensation : 46 LPA 🤩

 
 
𝐑𝐞𝐜𝐫𝐮𝐢𝐭𝐦𝐞𝐧𝐭 𝐏𝐫𝐨𝐜𝐞𝐬𝐬:
Amazon conducts 4 rounds to select freshers as SDE (SDE-1) in their organization off campus. The following rounds are conducted:
- Online Coding Round
- 2 Technical Rounds
- Bar Raiser round


 
𝐎𝐧𝐥𝐢𝐧𝐞 𝐂𝐨𝐝𝐢𝐧𝐠 𝐑𝐨𝐮𝐧𝐝:
This round is hosted online and the candidates are presented with 2 coding questions, the questions are of intermediate difficulty, mainly from Arrays, strings, and matrices.
To clear this round, one should have a strong understanding of these data structures.
Time given is 70 minutes. 
 
 

𝐓𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐑𝐨𝐮𝐧𝐝 1:
Technical rounds are face-to-face algorithmic rounds in which candidates are presented with 2-4 questions, all from data structures. The most commonly asked DSs are the matrix, binary tree, BST, and Linked list.
 
 
 
𝐓𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐑𝐨𝐮𝐧𝐝 2:
The same as the previous round, however, the difficulty is increased and more questions from Trees, BST, and Tries are asked. One should have a clear knowledge of tree-based recursion, and the standard questions based on it are a must. 
 

 
𝐁𝐚𝐫 𝐑𝐚𝐢𝐬𝐞𝐫 𝐑𝐨𝐮𝐧𝐝:
Amazon has 16 leadership principles and questions are asked on those, and generally, these questions are asked in all the interview round and especially in Bar raiser round along with 1-2 DSA problems.



𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐏𝐨𝐢𝐧𝐭𝐬 𝐭𝐨 𝐫𝐞𝐦𝐞𝐦𝐛𝐞𝐫 :
 
- Never postpone your interview(That might lead to many gaps in dates because multiple candidates are giving interviews.)
 
- Take the Bar Raiser round seriously(Always prepare for leadership principle questions, It is the most important round of the process.)
 
 - Always focus on concepts(Never mug up the questions, always try to understand the questions.)
 
- Be confident about your answers(Never doubt yourself in the interview.)
 
- Always try explaining your approach before coding(It would be a better practice if you give a brute force approach.)
 
- Have a good understanding of time complexity(I was also asked TC of every question.) 
 
 
 
Follow for more.
 
Happy Learning !! 


 
Tags -
#interviews #leetcode #questions #array #sorting #queue #loop #tree #graphs #amazon #sde #interviewpreparation #coding #computerscience #softwareengineer #workforwin #intern #internship #amazonindia #learning #softwaredevelopement #opportunity #dsa #faang #interview #amazonian

🚀 Empower your career with data engineering skills and secure your dream job in this growing field⚙️

✔️ After receiving a lot of queries, I've made some revisions to my original suggestion and I highly recommend following this exact sequence. Trust me, it will make things much easier for you.

♻️ It's easy to get lost in the vast amount of information available when it comes to learning new skills, especially in the field of data engineering.

🔗 However, with a solid roadmap and some dedication, it is possible to enter the field of data engineering in 2023.

Here are some steps you can follow to make sure you're on the right track -

🔶 Learn RDBMS, NoSQL databases, SQL, and data warehousing concepts :

As a data engineer, you'll be working with large amounts of data stored in databases. Familiarize yourself with different types of databases and how to query them using SQL. Learn one RDBMS and one NoSQL database, then familiarize yourself with data warehousing concepts.

1. Learn Data Warehousing concepts - https://lnkd.in/eKnVbFAB
2. Learn MySql - https://lnkd.in/efk-Mi3c
3. Learn and practice SQL - https://lnkd.in/efMKFkfX
4. Learn Azure Cosmos DB - https://lnkd.in/eNVyc6Mq
   
🔶 Learn Python and PySpark :

These are essential tools for data engineers.

1. Python: https://lnkd.in/e5rCbvP8
2. PySpark : https://bit.ly/3Vu34Ev

🔶 Learn Bash, Airflow and Kafka :

These tools will help you automate and streamline data processing tasks. You will also lear how to create data pipelines.🔩

https://lnkd.in/eyN6u2yd

🔶 Learn Git and the basics of CICD :

These skills will help you work collaboratively on data engineering projects and ensure smooth deployment.

Git - https://lnkd.in/eX_Q8s99
Basics of CICD - https://lnkd.in/epKGivFY

🔶 Learn Azure Databricks and Data Lakes :

Azure Databricks - https://lnkd.in/eBij4akJ
Learn Data Lakes - https://lnkd.in/eQ9xxAJT

👉 Create a standout resume by showcasing your skills and experience in data engineering.

👉 Enhance your portfolio by completing various data engineering projects and sharing them on GitHub.

👉 Seek out opportunities in data engineering by applying to relevant positions

Optional Learning -

1. Learn Data Structure and Algorithms
2. Learn AWS or Azure services dedicated for data engineering works.
   
By following these steps and dedicating yourself to learning and gaining experience, you can become a data engineer in 2023. Good luck on your journey!

I have created a Telegram channel for sharing knowledge and have included the link in the comments section.

📌 If you like my posts, please follow https://www.linkedin.com/groups/14161672 🇺🇸 🌐🌐 and hit the 🔔 on my profile to get a notification for all my new posts.

#dataengineering #nosql #hadoop #datastructures #sql #algorithms #bigdata #business #python #data #programming #mysql #database #aws #spark #github #azure #job #career #learning #opportunities #experience #resume #engineer #warehousing