Data Engineers

Data Analytics Interview Topics in structured way : 🔵Python: Data Structures: Lists, tuples, dictionaries, sets Pandas: Data manipulation (DataFrame operations, merging, reshaping) NumPy: Numeric computing, arrays Visualization: Matplotlib, Seaborn for creating charts 🔵SQL: Basic : SELECT, WHERE, JOIN, GROUP BY, ORDER BY Advanced : Subqueries, nested queries, window functions DBMS: Creating tables, altering schema, indexing Joins: Inner join, outer join, left/right join Data Manipulation: UPDATE, DELETE, INSERT statements Aggregate Functions: SUM, AVG, COUNT, MAX, MIN 🔵Excel: Formulas & Functions: VLOOKUP, HLOOKUP, IF, SUMIF, COUNTIF Data Cleaning: Removing duplicates, handling errors, text-to-columns PivotTables Charts and Graphs What-If Analysis: Scenario Manager, Goal Seek, Solver 🔵Power BI: Data Modeling: Creating relationships between datasets Transformation: Cleaning & shaping data using Power Query Editor Visualization: Creating interactive reports and dashboards DAX (Data Analysis Expressions): Formulas for calculated columns, measures Publishing and sharing reports, scheduling data refresh 🔵 Statistics Fundamentals: Mean, median, mode Variance, standard deviation Probability distributions Hypothesis testing, p-values, confidence intervals 🔵Data Manipulation and Cleaning: Data preprocessing techniques (handling missing values, outliers), Data normalization and standardization Data transformation Handling categorical data 🔵Data Visualization: Chart types (bar, line, scatter, histogram, boxplot) Data visualization libraries (matplotlib, seaborn, ggplot) Effective data storytelling through visualization Also showcase these skills using data portfolio if possible Like for more content like this 😍

𝟳 𝗕𝗲𝘀𝘁 𝗙𝗿𝗲𝗲 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 & 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲 𝗣𝘆𝘁𝗵𝗼𝗻 𝗳𝗼𝗿 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀😍 💻 You don’t need to spend a rupee to master Python!🐍 Whether you’re an aspiring Data Analyst, Developer, or Tech Enthusiast, these 7 completely free platforms help you go from zero to confident coder👨‍💻📌 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4l5XXY2 Enjoy Learning ✅️

Python Advanced Project Ideas 💡

🙏💸 500$ FOR THE FIRST 500 WHO JOIN THE CHANNEL! 🙏💸 Join our channel today for free! Tomorrow it will cost 500$! https://t.me/+104RMnxC7U1kZTll You can join at this link! 👆👇 https://t.me/+104RMnxC7U1kZTll

Coding and Aptitude Round before interview Coding challenges are meant to test your coding skills (especially if you are applying for ML engineer role). The coding challenges can contain algorithm and data structures problems of varying difficulty. These challenges will be timed based on how complicated the questions are. These are intended to test your basic algorithmic thinking. Sometimes, a complicated data science question like making predictions based on twitter data are also given. These challenges are hosted on HackerRank, HackerEarth, CoderByte etc. In addition, you may even be asked multiple-choice questions on the fundamentals of data science and statistics. This round is meant to be a filtering round where candidates whose fundamentals are little shaky are eliminated. These rounds are typically conducted without any manual intervention, so it is important to be well prepared for this round. Sometimes a separate Aptitude test is conducted or along with the technical round an aptitude test is also conducted to assess your aptitude skills. A Data Scientist is expected to have a good aptitude as this field is continuously evolving and a Data Scientist encounters new challenges every day. If you have appeared for GMAT / GRE or CAT, this should be easy for you. Resources for Prep: For algorithms and data structures prep,Leetcode and Hackerrank are good resources. For aptitude prep, you can refer to IndiaBixand Practice Aptitude. With respect to data science challenges, practice well on GLabs and Kaggle. Brilliant is an excellent resource for tricky math and statistics questions. For practising SQL, SQL Zoo and Mode Analytics are good resources that allow you to solve the exercises in the browser itself. Things to Note: Ensure that you are calm and relaxed before you attempt to answer the challenge. Read through all the questions before you start attempting the same. Let your mind go into problem-solving mode before your fingers do! In case, you are finished with the test before time, recheck your answers and then submit. Sometimes these rounds don’t go your way, you might have had a brain fade, it was not your day etc. Don’t worry! Shake if off for there is always a next time and this is not the end of the world.

𝗧𝗼𝗽 𝗧𝗲𝗰𝗵 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 - 𝗖𝗿𝗮𝗰𝗸 𝗬𝗼𝘂𝗿 𝗡𝗲𝘅𝘁 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄😍 𝗦𝗤𝗟:- https://pdlink.in/3SMHxaZ 𝗣𝘆𝘁𝗵𝗼𝗻 :- https://pdlink.in/3FJhizk 𝗝𝗮𝘃𝗮  :- https://pdlink.in/4dWkAMf 𝗗𝗦𝗔 :- https://pdlink.in/3FsDA8j  𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 :- https://pdlink.in/4jLOJ2a 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 :-  https://pdlink.in/4dFem3o 𝗖𝗼𝗱𝗶𝗻𝗴 :- https://pdlink.in/3F00oMw Get Your Dream Tech Job In Your Dream Company💫

Seaborn Cheatsheet ✅

𝗙𝗿𝗲𝗲 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗥𝗼𝗮𝗱𝗺𝗮𝗽 𝗳𝗼𝗿 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿𝘀: 𝟱 𝗦𝘁𝗲𝗽𝘀 𝘁𝗼 𝗦𝘁𝗮𝗿𝘁 𝗬𝗼𝘂𝗿 𝗝𝗼𝘂𝗿𝗻𝗲𝘆😍 Want to break into Data Science but don’t know where to begin?👨‍💻📌 You’re not alone. Data Science is one of the most in-demand fields today, but with so many courses online, it can feel overwhelming.💫📲 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/3SU5FJ0 No prior experience needed!✅️

10 ChatGPT Prompts for Marketing You'll Actually Use: 1. Crafting a Brand Story Prompt: "Develop an engaging brand story and persona for [company name] that authentically conveys our mission, values, and competitive differentiation." 2. Optimizing Landing Pages Prompt: "Optimize the landing page for [product/service page name] to immediately convey value, build trust, and motivate visitors to convert." 3. Generating Content Ideas Prompt: "Suggest 10 compelling content ideas related to [topic/keyword] that will engage our target audience and promote brand awareness." 4. Improving SEO Prompt: "Provide 3 strategic recommendations to improve SEO and increase organic traffic for [company name/website]." 5. Building an Email Nurture Sequence Prompt: "Design a personalized, multi-message email nurture sequence focused on educating and converting leads interested in [product/service]." 6. Crafting Value Propositions Prompt: "Create strong, benefit-driven value propositions highlighting the top 3 advantages of using [product/service] over competitors." 7. Producing Engaging Social Media Content Prompt: "Develop 5 creative social media post ideas for [platform] that will resonate with our audience and align with broader campaign goals." 8. Planning an Influencer Marketing Partnership Prompt: "Outline an influencer partnership strategy for [company] to build brand awareness and trust among our target demographic." 9. Crafting Paid Ads Prompt: "Write high-converting Facebook/Google ads for [product/service] tailored to our unique selling proposition and audience motivations." 10. Building an Email Marketing Campaign Prompt: "Construct a complete email marketing campaign for the launch of [product/service], including series copy, visual assets, send schedule, and success metrics." Share with your friends: https://t.me/Learn_Startup ENJOY LEARNING 👍👍

𝟱 𝗙𝗿𝗲𝗲 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗳𝗿𝗼𝗺 𝗦𝗰𝗿𝗮𝘁𝗰𝗵 𝗶𝗻 𝟮𝟬𝟮𝟱😍 🎯 Want to break into Machine Learning but don’t know where to start?✨️ You don’t need a fancy degree or expensive course to begin your ML journey📊 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4jRouYb This list is for anyone ready to start learning ML from scratch✅️

𝟭𝟬𝟬% 𝗙𝗿𝗲𝗲 𝗧𝗲𝗰𝗵 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍 From data science and AI to web development and cloud computing, checkout Top 5 Websites for Free Tech Certification Courses in 2025 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4e76jMX Enroll For FREE & Get Certified!✅️

🧠 Technologies for Data Analysts! 📊 Data Manipulation & Analysis ▪️ Excel – Spreadsheet Data Analysis & Visualization ▪️ SQL – Structured Query Language for Data Extraction ▪️ Pandas (Python) – Data Analysis with DataFrames ▪️ NumPy (Python) – Numerical Computing for Large Datasets ▪️ Google Sheets – Online Collaboration for Data Analysis 📈 Data Visualization ▪️ Power BI – Business Intelligence & Dashboarding ▪️ Tableau – Interactive Data Visualization ▪️ Matplotlib (Python) – Plotting Graphs & Charts ▪️ Seaborn (Python) – Statistical Data Visualization ▪️ Google Data Studio – Free, Web-Based Visualization Tool 🔄 ETL (Extract, Transform, Load) ▪️ SQL Server Integration Services (SSIS) – Data Integration & ETL ▪️ Apache NiFi – Automating Data Flows ▪️ Talend – Data Integration for Cloud & On-premises 🧹 Data Cleaning & Preparation ▪️ OpenRefine – Clean & Transform Messy Data ▪️ Pandas Profiling (Python) – Data Profiling & Preprocessing ▪️ DataWrangler – Data Transformation Tool 📦 Data Storage & Databases ▪️ SQL – Relational Databases (MySQL, PostgreSQL, MS SQL) ▪️ NoSQL (MongoDB) – Flexible, Schema-less Data Storage ▪️ Google BigQuery – Scalable Cloud Data Warehousing ▪️ Redshift – Amazon’s Cloud Data Warehouse ⚙️ Data Automation ▪️ Alteryx – Data Blending & Advanced Analytics ▪️ Knime – Data Analytics & Reporting Automation ▪️ Zapier – Connect & Automate Data Workflows 📊 Advanced Analytics & Statistical Tools ▪️ R – Statistical Computing & Analysis ▪️ Python (SciPy, Statsmodels) – Statistical Modeling & Hypothesis Testing ▪️ SPSS – Statistical Software for Data Analysis ▪️ SAS – Advanced Analytics & Predictive Modeling 🌐 Collaboration & Reporting ▪️ Power BI Service – Online Sharing & Collaboration for Dashboards ▪️ Tableau Online – Cloud-Based Visualization & Sharing ▪️ Google Analytics – Web Traffic Data Insights ▪️ Trello / JIRA – Project & Task Management for Data Projects Data-Driven Decisions with the Right Tools! React ❤️ for more

𝗙𝗿𝗲𝗲 𝗣𝘆𝘁𝗵𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲: 𝗧𝗵𝗲 𝗕𝗲𝘀𝘁 𝗦𝘁𝗮𝗿𝘁𝗶𝗻𝗴 𝗣𝗼𝗶𝗻𝘁 𝗳𝗼𝗿 𝗧𝗲𝗰𝗵 & 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿𝘀😍 🚀 Want to break into tech or data analytics but don’t know how to start?📌✨️ Python is the #1 most in-demand programming language, and Scaler’s free Python for Beginners course is a game-changer for absolute beginners📊✔️ 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/45TroYX No coding background needed!✅️

Planning for Data Science or Data Engineering Interview. Focus on SQL & Python first. Here are some important questions which you should know. 𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐒𝐐𝐋 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬 1- Find out nth Order/Salary from the tables. 2- Find the no of output records in each join from given Table 1 & Table 2 3- YOY,MOM Growth related questions. 4- Find out Employee ,Manager Hierarchy (Self join related question) or Employees who are earning more than managers. 5- RANK,DENSERANK related questions 6- Some row level scanning medium to complex questions using CTE or recursive CTE, like (Missing no /Missing Item from the list etc.) 7- No of matches played by every team or Source to Destination flight combination using CROSS JOIN. 8-Use window functions to perform advanced analytical tasks, such as calculating moving averages or detecting outliers. 9- Implement logic to handle hierarchical data, such as finding all descendants of a given node in a tree structure. 10-Identify and remove duplicate records from a table. 𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐏𝐲𝐭𝐡𝐨𝐧 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬 1- Reversing a String using an Extended Slicing techniques. 2- Count Vowels from Given words . 3- Find the highest occurrences of each word from string and sort them in order. 4- Remove Duplicates from List. 5-Sort a List without using Sort keyword. 6-Find the pair of numbers in this list whose sum is n no. 7-Find the max and min no in the list without using inbuilt functions. 8-Calculate the Intersection of Two Lists without using Built-in Functions 9-Write Python code to make API requests to a public API (e.g., weather API) and process the JSON response. 10-Implement a function to fetch data from a database table, perform data manipulation, and update the database. Join for more: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D ENJOY LEARNING 👍👍

𝟭𝟬𝟬𝟬+ 𝗙𝗿𝗲𝗲 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗲𝗱 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗯𝘆 𝗜𝗻𝗳𝗼𝘀𝘆𝘀 – 𝗟𝗲𝗮𝗿𝗻, 𝗚𝗿𝗼𝘄, 𝗦𝘂𝗰𝗰𝗲𝗲𝗱!😍 🚀 Looking to upgrade your skills without spending a rupee?💰 Here’s your golden opportunity to unlock 1,000+ certified online courses across technology, business, communication, leadership, soft skills, and much more — all absolutely FREE on Infosys Springboard!🔥 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/43UcmQ7 Save this blog, sign up, and start your upskilling journey today!✅️

𝟰 𝗛𝗶𝗴𝗵-𝗜𝗺𝗽𝗮𝗰𝘁 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝘁𝗼 𝗟𝗮𝘂𝗻𝗰𝗵 𝗬𝗼𝘂𝗿 𝗖𝗮𝗿𝗲𝗲𝗿 𝗶𝗻 𝟮𝟬𝟮𝟱😍 These globally recognized certifications from platforms like Google, IBM, Microsoft, and DataCamp are beginner-friendly, industry-aligned, and designed to make you job-ready in just a few weeks 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4kC18XE These courses help you gain hands-on experience — exactly what top MNCs look for!✅️

Machine Learning Algorithms every data scientist should know: 📌 Supervised Learning: 🔹 Regression ∟ Linear Regression ∟ Ridge & Lasso Regression ∟ Polynomial Regression 🔹 Classification ∟ Logistic Regression ∟ K-Nearest Neighbors (KNN) ∟ Decision Tree ∟ Random Forest ∟ Support Vector Machine (SVM) ∟ Naive Bayes ∟ Gradient Boosting (XGBoost, LightGBM, CatBoost) 📌 Unsupervised Learning: 🔹 Clustering ∟ K-Means ∟ Hierarchical Clustering ∟ DBSCAN 🔹 Dimensionality Reduction ∟ PCA (Principal Component Analysis) ∟ t-SNE ∟ LDA (Linear Discriminant Analysis) 📌 Reinforcement Learning (Basics): ∟ Q-Learning ∟ Deep Q Network (DQN) 📌 Ensemble Techniques: ∟ Bagging (Random Forest) ∟ Boosting (XGBoost, AdaBoost, Gradient Boosting) ∟ Stacking Don’t forget to learn model evaluation metrics: accuracy, precision, recall, F1-score, AUC-ROC, confusion matrix, etc. Free Machine Learning Resources: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D React ❤️ for more free resources

𝐈𝐁𝐌 𝐅𝐑𝐄𝐄 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐮𝐫𝐬𝐞𝐬😍 🚀 Dive into the world of Data Analytics with these 6 free courses by IBM! Gain practical knowledge and stand out in your career with tools designed for real-world applications. All courses come with expert guidance and are free to access!🎉 𝐋𝐢𝐧𝐤 👇:-    https://bit.ly/4iXOmmb   Enroll For FREE & Get Certified 🎓

Amazon Interview Process for Data Scientist position 📍Round 1- Phone Screen round This was a preliminary round to check my capability, projects to coding, Stats, ML, etc. After clearing this round the technical Interview rounds started. There were 5-6 rounds (Multiple rounds in one day). 📍 𝗥𝗼𝘂𝗻𝗱 𝟮- 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗕𝗿𝗲𝗮𝗱𝘁𝗵: In this round the interviewer tested my knowledge on different kinds of topics. 📍𝗥𝗼𝘂𝗻𝗱 𝟯- 𝗗𝗲𝗽𝘁𝗵 𝗥𝗼𝘂𝗻𝗱: In this round the interviewers grilled deeper into 1-2 topics. I was asked questions around: Standard ML tech, Linear Equation, Techniques, etc. 📍𝗥𝗼𝘂𝗻𝗱 𝟰- 𝗖𝗼𝗱𝗶𝗻𝗴 𝗥𝗼𝘂𝗻𝗱- This was a Python coding round, which I cleared successfully. 📍𝗥𝗼𝘂𝗻𝗱 𝟱- This was 𝗛𝗶𝗿𝗶𝗻𝗴 𝗠𝗮𝗻𝗮𝗴𝗲𝗿 where my fitment for the team got assessed. 📍𝗟𝗮𝘀𝘁 𝗥𝗼𝘂𝗻𝗱- 𝗕𝗮𝗿 𝗥𝗮𝗶𝘀𝗲𝗿- Very important round, I was asked heavily around Leadership principles & Employee dignity questions. So, here are my Tips if you’re targeting any Data Science role: -> Never make up stuff & don’t lie in your Resume. -> Projects thoroughly study. -> Practice SQL, DSA, Coding problem on Leetcode/Hackerank. -> Download data from Kaggle & build EDA (Data manipulation questions are asked) Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624 ENJOY LEARNING 👍👍

𝗟𝗲𝗮𝗿𝗻 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘 𝘄𝗶𝘁𝗵 𝗛𝗮𝗿𝘃𝗮𝗿𝗱 𝗨𝗻𝗶𝘃𝗲𝗿𝘀𝗶𝘁𝘆😍 🎯 Want to break into Data Science without spending a single rupee?💰 Harvard University is offering a goldmine of free courses that make top-tier education accessible to anyone, anywhere👨‍💻✨️ 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/3HxOgTW These courses are designed by Ivy League experts and are trusted by thousands globally✅️