Data Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources

If you want to be a data analyst, you should work to become as good at SQL as possible. 1. SELECT What a surprise! I need to choose what data I want to return. 2. FROM Again, no shock here. I gotta choose what table I am pulling my data from. 3. WHERE This is also pretty basic, but I almost always filter the data to whatever range I need and filter the data to whatever condition I’m looking for. 4. JOIN This may surprise you that the next one isn’t one of the other core SQL clauses, but at least for my work, I utilize some kind of join in almost every query I write. 5. Calculations This isn’t necessarily a function of SQL, but I write a lot of calculations in my queries. Common examples include finding the time between two dates and multiplying and dividing values to get what I need. Add operators and a couple data cleaning functions and that’s 80%+ of the SQL I write on the job.

𝟰 𝗙𝗥𝗘𝗘 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗯𝘆 𝗛𝗮𝗿𝘃𝗮𝗿𝗱 𝗮𝗻𝗱 𝗦𝘁𝗮𝗻𝗳𝗼𝗿𝗱 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝗔𝗜😍 Dreaming of Mastering AI? 🎯 Harvard and Stanford—two of the most prestigious universities in the world—are offering FREE AI courses👨‍💻 No hidden fees, no long applications—just pure, world-class education, accessible to everyone🔥 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/3GqHkau Here’s your golden ticket to the future!✅

𝗪𝗮𝗻𝘁 𝘁𝗼 𝗸𝗻𝗼𝘄 𝘄𝗵𝗮𝘁 𝗵𝗮𝗽𝗽𝗲𝗻𝘀 𝗶𝗻 𝗮 𝗿𝗲𝗮𝗹 𝗱𝗮𝘁𝗮 𝗮𝗻𝗮𝗹𝘆𝘀𝘁 𝗶𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄? 𝗕𝗮𝘀𝗶𝗰 𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 -Brief introduction about yourself. -Explanation of how you developed an interest in learning Power BI despite having a chemical background. 𝗧𝗼𝗼𝗹𝘀 𝗣𝗿𝗼𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 -Discussion about the tools you are proficient in. -Detailed explanation of a project that demonstrated your proficiency in these tools. 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗘𝘅𝗽𝗹𝗮𝗻𝗮𝘁𝗶𝗼𝗻 Explain about any Data Analytics Project you did, below are some follow-up questions for sales related data analysis project Follow-up Question: Was there any improvement in sales after building the report? Provide a clear before and after scenario in sales post-report creation. What areas did you identify where the company was losing sales, and what were your recommendations? - How do you check the quality of data when it's given to you? Explain your methods for ensuring data quality. - How do you handle null values? Describe your approach to managing null values in datasets. 𝗦𝗤𝗟 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 -Explain the order in which SQL clauses are executed. -Write a query to find the percentage of the 18-year-old population. Details: You are given two tables: Table 1: Contains states and their respective populations. Table 2: Contains three columns (state, gender, and population of 18-year-olds). -Explain window functions and how to rank values in SQL. - Difference between JOIN and UNION. -How to return unique values in SQL. 𝗕𝗲𝗵𝗮𝘃𝗶𝗼𝗿𝗮𝗹 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 -Solve a puzzle involving 3 gallons of water in one jar and 2 gallons in another to get exactly 4 gallons. Step-by-step solution for the water puzzle. - What skills have you learned on your own? Discuss the skills you self-taught and their impact on your career. -Describe cases when you showcased team spirit. -⭐ 𝗦𝗼𝗰𝗶𝗮𝗹 𝗠𝗲𝗱𝗶𝗮 𝗔𝗽𝗽 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻 Scenario: Choose any social media app (I choose Discord). Question: What function/feature would you add to the Discord app, and how would you track its success? - Rate yourself on Excel, SQL, and Python out of 10. - What are your strengths in data analytics? I have curated best 80+ top-notch Data Analytics Resources 👇👇 https://whatsapp.com/channel/0029VaGgzAk72WTmQFERKh02 Like if it helps :)

𝟱 𝗙𝗥𝗘𝗘 𝗜𝗕𝗠 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘁𝗼 𝗦𝗸𝘆𝗿𝗼𝗰𝗸𝗲𝘁 𝗬𝗼𝘂𝗿 𝗥𝗲𝘀𝘂𝗺𝗲😍 From mastering Cloud Computing to diving into Deep Learning, Docker, Big Data, and IoT Blockchain IBM, one of the biggest tech companies, is offering 5 FREE courses that can seriously upgrade your resume and skills — without costing you anything. 𝗟𝗶𝗻𝗸:-👇 https://pdlink.in/44GsWoC Enroll For FREE & Get Certified ✅

MUST ADD these 5 POWER Bl projects to your resume to get hired Here are 5 mini projects that not only help you to gain experience but also it will help you to build your resume stronger 📌Customer Churn Analysis 🔗 https://www.kaggle.com/code/fabiendaniel/customer-segmentation/input 📌Credit Card Fraud 🔗 https://www.kaggle.com/datasets/mlg-ulb/creditcardfraud 📌Movie Sales Analysis 🔗https://www.kaggle.com/datasets/PromptCloudHQ/imdb-data 📌Airline Sector 🔗https://www.kaggle.com/datasets/yuanyuwendymu/airline- 📌Financial Data Analysis 🔗https://www.kaggle.com/datasets/qks1%7Cver/financial-data- Simple guide 1. Data Utilization: - Initiate the process by using the provided datasets for a comprehensive analysis. 2. Domain Research: - Conduct thorough research within the domain to identify crucial metrics and KPIs for analysis. 3. Dashboard Blueprint: - Outline the structure and aesthetics of your dashboard, drawing inspiration from existing online dashboards for enhanced design and functionality. 4. Data Handling: - Import data meticulously, ensuring accuracy. Proceed with cleaning, modeling, and the creation of essential measures and calculations. 5. Question Formulation: - Brainstorm a list of insightful questions your dashboard aims to answer, covering trends, comparisons, aggregations, and correlations within the data. 6. Platform Integration: - Utilize Novypro.com as the hosting platform for your dashboard, ensuring seamless integration and accessibility. 7. LinkedIn Visibility: - Share your dashboard on LinkedIn with a concise post providing context. Include a link to your Novypro-hosted dashboard to foster engagement and professional connections. Join for more: https://t.me/DataPortfolio Hope this helps you :)

𝟲 𝗕𝗲𝘀𝘁 𝗬𝗼𝘂𝗧𝘂𝗯𝗲 𝗖𝗵𝗮𝗻𝗻𝗲𝗹𝘀 𝘁𝗼 𝗠𝗮𝘀𝘁𝗲𝗿 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜😍 Power BI Isn’t Just a Tool—It’s a Career Game-Changer🚀 Whether you’re a student, a working professional, or switching careers, learning Power BI can set you apart in the competitive world of data analytics📊 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/3ELirpu Your Analytics Journey Starts Now✅️

Skills need for everyday data analysis jobs

𝗧𝗖𝗦 𝗙𝗥𝗘𝗘 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍 Want to kickstart your career in Data Analytics but don’t know where to begin?👨‍💻 TCS has your back with a completely FREE course designed just for beginners✅ 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4jNMoEg Just pure, job-ready learning📍

🔟 Project Ideas for a data analyst Customer Segmentation: Analyze customer data to segment them based on their behaviors, preferences, or demographics, helping businesses tailor their marketing strategies. Churn Prediction: Build a model to predict customer churn, identifying factors that contribute to churn and proposing strategies to retain customers. Sales Forecasting: Use historical sales data to create a predictive model that forecasts future sales, aiding inventory management and resource planning. Market Basket Analysis: Analyze transaction data to identify associations between products often purchased together, assisting retailers in optimizing product placement and cross-selling. Sentiment Analysis: Analyze social media or customer reviews to gauge public sentiment about a product or service, providing valuable insights for brand reputation management. Healthcare Analytics: Examine medical records to identify trends, patterns, or correlations in patient data, aiding in disease prediction, treatment optimization, and resource allocation. Financial Fraud Detection: Develop algorithms to detect anomalous transactions and patterns in financial data, helping prevent fraud and secure transactions. A/B Testing Analysis: Evaluate the results of A/B tests to determine the effectiveness of different strategies or changes on websites, apps, or marketing campaigns. Energy Consumption Analysis: Analyze energy usage data to identify patterns and inefficiencies, suggesting strategies for optimizing energy consumption in buildings or industries. Real Estate Market Analysis: Study housing market data to identify trends in property prices, rental rates, and demand, assisting buyers, sellers, and investors in making informed decisions. Remember to choose a project that aligns with your interests and the domain you're passionate about. Data Analyst Roadmap 👇👇 https://t.me/sqlspecialist/379 ENJOY LEARNING 👍👍

𝗪𝗮𝗻𝘁 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝗜𝗻-𝗗𝗲𝗺𝗮𝗻𝗱 𝗧𝗲𝗰𝗵 𝗦𝗸𝗶𝗹𝗹𝘀 — 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘 — 𝗗𝗶𝗿𝗲𝗰𝘁𝗹𝘆 𝗳𝗿𝗼𝗺 𝗚𝗼𝗼𝗴𝗹𝗲?😍 Whether you’re a student, job seeker, or just hungry to upskill — these 5 beginner-friendly courses are your golden ticket. 🎟️ Just career-boosting knowledge and certificates that make your resume pop📄 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/42vL6br All The Best 🎊

30 Days Python Roadmap for Data Analysts 👆

𝟱 𝗙𝗿𝗲𝗲 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝗧𝗵𝗮𝘁’𝗹𝗹 𝗠𝗮𝗸𝗲 𝗦𝗤𝗟 𝗙𝗶𝗻𝗮𝗹𝗹𝘆 𝗖𝗹𝗶𝗰𝗸.😍 SQL seems tough, right? 😩 These 5 FREE SQL resources will take you from beginner to advanced without boring theory dumps or confusion.📊 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/3GtntaC Master it with ease. 💡

Here are 5 key Python libraries/ concepts that are particularly important for data analysts: 1. Pandas: Pandas is a powerful library for data manipulation and analysis in Python. It provides data structures like DataFrames and Series that make it easy to work with structured data. Pandas offers functions for reading and writing data, cleaning and transforming data, and performing data analysis tasks like filtering, grouping, and aggregating. 2. NumPy: NumPy is a fundamental package for scientific computing in Python. It provides support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on these arrays efficiently. NumPy is often used in conjunction with Pandas for numerical computations and data manipulation. 3. Matplotlib and Seaborn: Matplotlib is a popular plotting library in Python that allows you to create a wide variety of static, interactive, and animated visualizations. Seaborn is built on top of Matplotlib and provides a higher-level interface for creating attractive and informative statistical graphics. These libraries are essential for data visualization in data analysis projects. 4. Scikit-learn: Scikit-learn is a machine learning library in Python that provides simple and efficient tools for data mining and data analysis tasks. It includes a wide range of algorithms for classification, regression, clustering, dimensionality reduction, and more. Scikit-learn also offers tools for model evaluation, hyperparameter tuning, and model selection. 5. Data Cleaning and Preprocessing: Data cleaning and preprocessing are crucial steps in any data analysis project. Python offers libraries like Pandas and NumPy for handling missing values, removing duplicates, standardizing data types, scaling numerical features, encoding categorical variables, and more. Understanding how to clean and preprocess data effectively is essential for accurate analysis and modeling. By mastering these Python concepts and libraries, data analysts can efficiently manipulate and analyze data, create insightful visualizations, apply machine learning techniques, and derive valuable insights from their datasets. Credits: https://t.me/free4unow_backup ENJOY LEARNING 👍👍

𝗡𝗼 𝗗𝗲𝗴𝗿𝗲𝗲? 𝗡𝗼 𝗣𝗿𝗼𝗯𝗹𝗲𝗺. 𝗧𝗵𝗲𝘀𝗲 𝟰 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝗖𝗮𝗻 𝗟𝗮𝗻𝗱 𝗬𝗼𝘂 𝗮 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁 𝗝𝗼𝗯😍 Dreaming of a career in data but don’t have a degree? You don’t need one. What you do need are the right skills🔗 These 4 free/affordable certifications can get you there. 💻✨ 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4ioaJ2p Let’s get you certified and hired!✅️

Free Resources 👇 Data Science: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D Data Analyst: https://whatsapp.com/channel/0029VaGgzAk72WTmQFERKh02 Data Engineers: https://whatsapp.com/channel/0029Vaovs0ZKbYMKXvKRYi3C

🌮 Data Analyst Vs Data Engineer Vs Data Scientist 🌮 Skills required to become data analyst 👉 Advanced Excel, Oracle/SQL 👉 Python/R Skills required to become data engineer 👉 Python/ Java. 👉 SQL, NoSQL technologies like Cassandra or MongoDB 👉 Big data technologies like Hadoop, Hive/ Pig/ Spark Skills required to become data Scientist 👉 In-depth knowledge of tools like R/ Python/ SAS. 👉 Well versed in various machine learning algorithms like scikit-learn, karas and tensorflow 👉 SQL and NoSQL Bonus skill required: Data Visualization (PowerBI/ Tableau) & Statistics

Want to practice for your next interview? Then use this prompt and ask Chat GPT to act as an interviewer 😄👇 (Tap to copy) I want you to act as an interviewer. I will be the candidate and you will ask me the interview questions for the position position. I want you to only reply as the interviewer. Do not write all the conservation at once. I want you to only do the interview with me. Ask me the questions and wait for my answers. Do not write explanations. Ask me the questions one by one like an interviewer does and wait for my answers. My first sentence is "Hi" Now see how it goes. All the best for your preparation Like this post if you need more content like this👍❤️

𝗗𝗿𝗲𝗮𝗺 𝗝𝗼𝗯 𝗮𝘁 𝗚𝗼𝗼𝗴𝗹𝗲? 𝗧𝗵𝗲𝘀𝗲 𝟰 𝗙𝗥𝗘𝗘 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝗪𝗶𝗹𝗹 𝗛𝗲𝗹𝗽 𝗬𝗼𝘂 𝗚𝗲𝘁 𝗧𝗵𝗲𝗿𝗲😍 Dreaming of working at Google but not sure where to even begin?📍 Start with these FREE insider resources—from building a resume that stands out to mastering the Google interview process. 🎯 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/441GCKF Because if someone else can do it, so can you. Why not you? Why not now?✅️