Data Analytics Projects - SQL, Excel, Tableau, Python & Power BI Interview Resources

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Covering all technical and popular stuff about anything related to Data Science: AI, Big Data, Machine Learning, Statistics, general Math and the applications of former. Ads/ Promo: @love_data

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📈 Análisis del canal de Telegram Data Analytics Projects - SQL, Excel, Tableau, Python & Power BI Interview Resources

El canal Data Analytics Projects - SQL, Excel, Tableau, Python & Power BI Interview Resources (@sqlproject) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 39 490 suscriptores, ocupando la posición 4 752 en la categoría Educación y el puesto 10 399 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 39 490 suscriptores.

Según los últimos datos del 09 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 197, y en las últimas 24 horas de 10, conservando un alto alcance.

Estado de verificación: No verificado
Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.73%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.01% de reacciones respecto al total de suscriptores.
Alcance de las publicaciones: Cada publicación recibe en promedio 1 079 visualizaciones. En el primer día suele acumular 400 visualizaciones.
Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 3.
Intereses temáticos: El contenido se centra en temas clave como analytic, dataset, visualization, sql, learning.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Covering all technical and popular stuff about anything related to Data Science: AI, Big Data, Machine Learning, Statistics, general Math and the applications of former. Ads/ Promo: @love_data”

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 10 junio, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Educación.

39 490

Suscriptores

+1024 horas

+457 días

+19730 días

1 079

Visitas de la publicación

~ 40024 horas

~ 53848 horas

2.73%

Tasa de compromiso

~ 1

Mensajes por día

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Archivo de publicaciones

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Step-by-step guide to become a Data Analyst in 2025—📊 1. Learn the Fundamentals: Start with Excel, basic statistics, and data visualization concepts. 2. Pick Up Key Tools & Languages: Master SQL, Python (or R), and data visualization tools like Tableau or Power BI. 3. Get Formal Education or Certification: A bachelor’s degree in a relevant field (like Computer Science, Math, or Economics) helps, but you can also do online courses or certifications in data analytics. 4. Build Hands-on Experience: Work on real-world projects—use Kaggle datasets, internships, or freelance gigs to practice data cleaning, analysis, and visualization. 5. Create a Portfolio: Showcase your projects on GitHub or a personal website. Include dashboards, reports, and code samples. 6. Develop Soft Skills: Focus on communication, problem-solving, teamwork, and attention to detail—these are just as important as technical skills. 7. Apply for Entry-Level Jobs: Look for roles like “Junior Data Analyst” or “Business Analyst.” Tailor your resume to highlight your skills and portfolio. 8. Keep Learning: Stay updated with new tools (like AI-driven analytics), trends, and advanced topics such as machine learning or domain-specific analytics. React ❤️ for more

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𝟭𝟬𝟬% 𝗙𝗥𝗘𝗘 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 😍 Master in-demand skills like Excel, SQL, Power BI & Data Visualization with 100% FREE Certification 💯 ✅ Industry-Relevant Curriculum ✅ No Cost – Lifetime Free Access ✅ Boost Your Resume & Job Readiness Perfect for Students, Freshers & Career Switchers! 𝐋𝐢𝐧𝐤 👇:- https://pdlink.in/4lp7hXQ 🎓 Enroll Now & Get Certified

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𝗠𝗮𝘀𝘁𝗲𝗿 𝗦𝗼𝗳𝘁 𝗦𝗸𝗶𝗹𝗹𝘀 𝗳𝗼𝗿 𝗖𝗮𝗿𝗲𝗲𝗿 𝗦𝘂𝗰𝗰𝗲𝘀𝘀!😍 Want to stand out in your career? Soft skills are just as important as technical expertise! 🌟 Here are 3 FREE courses to help you communicate, negotiate, and present with confidence🧑‍💻✨️ 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/41V1Yqi Tag someone who needs this boost! 🚀

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🎓 𝗖𝗶𝘀𝗰𝗼 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 – 𝗟𝗶𝗺𝗶𝘁𝗲𝗱 𝗧𝗶𝗺𝗲! 😍 Upskill in today’s most in-demand tech domains and boost your career 🚀 ✅ FREE Courses Offered: 🧠 Modern AI 🔐 Cyber Security 🌐 Networking 📲 Internet of Things (IoT) 💫Perfect for students, freshers, and tech enthusiasts. 𝗘𝗻𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇:- https://pdlink.in/45WnGy1 🎓 Get Certified by Cisco – 100% Free!

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What are the differences between a Power BI dataset, a Report, and a Dashboard? In Power BI: 1. Dataset: It's where your raw data resides. Think of it as your data source. You import or connect to data, transform it, and then store it in a dataset within Power BI. 2. Report: Reports visualize data from your dataset. They consist of visuals like charts, graphs, tables, etc., created using the data in your dataset. Reports allow you to explore and analyze your data in depth. 3. Dashboard: Dashboards are a collection of visuals from one or more reports, designed to give a snapshot view of your data. They provide a high-level overview of key metrics and trends. You can pin visuals from different reports onto a dashboard to create a unified view. I have curated the best interview resources to crack Power BI Interviews 👇👇 https://whatsapp.com/channel/0029Vai1xKf1dAvuk6s1v22c Hope you'll like it Like this post if you need more resources like this 👍❤️

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𝗧𝗼𝗽 𝟱 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀 𝗧𝗼 𝗠𝗮𝘀𝘁𝗲𝗿 𝗜𝗻 𝟮𝟬𝟮𝟱 | 𝗘𝗻𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘 😍 Acquire industry-relevant skills to grow in your career and stand out to prospective employers. 𝗔𝗜 & 𝗠𝗟 :- https://pdlink.in/3U3eZuq 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 :- https://pdlink.in/4lp7hXQ 𝗖𝗹𝗼𝘂𝗱 𝗖𝗼𝗺𝗽𝘂𝘁𝗶𝗻𝗴 :- https://pdlink.in/3GtNJlO 𝗖𝘆𝗯𝗲𝗿 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 :- https://pdlink.in/4nHBuTh 𝗙𝘂𝗹𝗹𝘀𝘁𝗮𝗰𝗸 :- https://pdlink.in/3ImMFAB Enroll For FREE & Get Certified 🎓

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𝟯 𝗙𝗿𝗲𝗲 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝘄𝗶𝘁𝗵 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗲𝘀 𝗕𝗼𝗼𝘀𝘁 𝗬𝗼𝘂𝗿 𝗖𝗮𝗿𝗲𝗲𝗿 𝗶𝗻 𝟮𝟬𝟮𝟱😍 Want to earn free certificates and badges from Microsoft? 🚀 These courses are your golden ticket to mastering in-demand tech skills while boosting your resume with official Microsoft credentials🧑‍💻📌 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4mlCvPu These certifications will help you stand out in interviews and open new career opportunities in tech✅️

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5 Essential Portfolio Projects for data analysts 😄👇 1. Exploratory Data Analysis (EDA) on a Real Dataset: Choose a dataset related to your interests, perform thorough EDA, visualize trends, and draw insights. This showcases your ability to understand data and derive meaningful conclusions. Free websites to find datasets: https://t.me/DataPortfolio/8 2. Predictive Modeling Project: Build a predictive model, such as a linear regression or classification model. Use a dataset to train and test your model, and evaluate its performance. Highlight your skills in machine learning and statistical analysis. 3. Data Cleaning and Transformation: Take a messy dataset and demonstrate your skills in cleaning and transforming data. Showcase your ability to handle missing values, outliers, and prepare data for analysis. 4. Dashboard Creation: Utilize tools like Tableau or Power BI to create an interactive dashboard. This project demonstrates your ability to present data insights in a visually appealing and user-friendly manner. 5. Time Series Analysis: Work with time-series data to forecast future trends. This could involve stock prices, weather data, or any other time-dependent dataset. Showcase your understanding of time-series concepts and forecasting techniques. Share with credits: https://t.me/sqlspecialist Like it if you need more posts like this 😄❤️ Hope it helps :)

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🎓 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 😍 Boost your tech skills with globally recognized Microsoft certifications: 🔹 Generative AI 🔹 Azure AI Fundamentals 🔹 Power BI 🔹 Computer Vision with Azure AI 🔹 Azure Developer Associate 🔹 Azure Security Engineer 𝗘𝗻𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇:- https://pdlink.in/45WnGy1 🎓 Get Certified | 🆓 100% Free

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Above attached is 150 SQL queries for practice ❤️

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SQL Queries .pdf1.24 MB

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𝐋𝐞𝐚𝐫𝐧 𝐃𝐢𝐫𝐞𝐜𝐭𝐥𝐲 𝐟𝐫𝐨𝐦 𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭: 𝐉𝐨𝐢𝐧 𝐅𝐫𝐞𝐞 𝐖𝐨𝐫𝐤𝐬𝐡𝐨𝐩𝐬 & 𝐓𝐞𝐜𝐡 𝐄𝐯𝐞𝐧𝐭𝐬 𝐯𝐢𝐚 𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭 𝐑𝐞𝐚𝐜𝐭𝐨𝐫😍 💻 Want to learn directly from Microsoft — absolutely FREE?💥 Whether you’re a student, job seeker, or tech enthusiast, Microsoft Reactor is your go-to hub for high-quality, interactive learning experiences🧑‍💻✨️ 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/3SYfyW1 All in one place✅️ 💓 See for yourself: ➡️ Join our 24/7 Global News channel now and be always live-u... | InsideAds

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Dataset Name: Fruit Detection Dataset Basic Description: Multilabel Fruits Detection 📖 FULL DATASET DESCRIPTION: ================================== The dataset includes 8479 images of 6 different fruits(Apple, Grapes, Pineapple, Orange, Banana, and Watermelon). Fruits are annotated in YOLOv8 format. The following pre-processing was applied to each image: The following augmentation was applied to create 3 versions of each source image: The following transformations were applied to the bounding boxes of each image: 📥 DATASET DOWNLOAD INFORMATION ================================== 🔴 Dataset Size: Download dataset as zip (525 MB) 🔰 Direct dataset download link: https://www.kaggle.com/api/v1/datasets/download/lakshaytyagi01/fruit-detection 📊 Additional information: ================================== Total files: 17,000 Views: 26,500 Downloads: 4,298 📚 RELATED NOTEBOOKS: ================================== 1. 🍍🍌🍓 YOLO-NAS 🏎💨 Fruit Detection 🍇🍒🍊 | Upvotes: 163 URL: https://www.kaggle.com/code/harpdeci/yolo-nas-fruit-detection 2. K-Fold Cross Validation and YoloV8 | Upvotes: 58 URL: https://www.kaggle.com/code/tataganesh/k-fold-cross-validation-and-yolov8 3. Fruits_objectdetection 🍍🍎 | Upvotes: 44 URL: https://www.kaggle.com/code/maryamayman20/fruits-objectdetection 4. Comprehensive Fruit Image Dataset | Upvotes: 13 URL: https://www.kaggle.com/datasets/evilspirit05/comprehensive-fruit-image-dataset 5. Fruit Infection Disease Dataset | Upvotes: 11 URL: https://www.kaggle.com/datasets/nikitkashyap/fruit-infection-disease-dataset ============================

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Essential SQL Topics for Data Analysts SQL for Data Analysts Free Resources -> https://t.me/sqlanalyst - Basic Queries: SELECT, FROM, WHERE clauses. - Sorting and Filtering: ORDER BY, GROUP BY, HAVING. - Joins: INNER JOIN, LEFT JOIN, RIGHT JOIN. - Aggregation Functions: COUNT, SUM, AVG, MIN, MAX. - Subqueries: Embedding queries within queries. - Data Modification: INSERT, UPDATE, DELETE. - Indexes: Optimizing query performance. - Normalization: Ensuring efficient database design. - Views: Creating virtual tables for simplified queries. - Understanding Database Relationships: One-to-One, One-to-Many, Many-to-Many. Window functions are also important for data analysts. They allow for advanced data analysis and manipulation within specified subsets of data. Commonly used window functions include: - ROW_NUMBER(): Assigns a unique number to each row based on a specified order. - RANK() and DENSE_RANK(): Rank data based on a specified order, handling ties differently. - LAG() and LEAD(): Access data from preceding or following rows within a partition. - SUM(), AVG(), MIN(), MAX(): Aggregations over a defined window of rows. Here is an amazing resources to learn & practice SQL: https://bit.ly/3FxxKPz Share with credits: https://t.me/sqlspecialist Hope it helps :)

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🤔Are you looking for some new project ideas to include in your Portfolio❓ 👉 Here are 3 unique ideas for you: 1️⃣ Summer Olympics Dataset : https://www.kaggle.com/datasets/divyansh22/summer-olympics-medals 2️⃣ Food Nutrition Dataset : https://www.kaggle.com/datasets/utsavdey1410/food-nutrition-dataset/data 3️⃣ Mental health Dataset : https://www.kaggle.com/datasets/programmerrdai/mental-health-dataset/data

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Machine Learning Algorithm: 1. Linear Regression: - Imagine drawing a straight line on a graph to show the relationship between two things, like how the height of a plant might relate to the amount of sunlight it gets. 2. Decision Trees: - Think of a game where you have to answer yes or no questions to find an object. It's like a flowchart helping you decide what the object is based on your answers. 3. Random Forest: - Picture a group of friends making decisions together. Random Forest is like combining the opinions of many friends to make a more reliable decision. 4. Support Vector Machines (SVM): - Imagine drawing a line to separate different types of things, like putting all red balls on one side and blue balls on the other, with the line in between them. 5. k-Nearest Neighbors (kNN): - Pretend you have a collection of toys, and you want to find out which toys are similar to a new one. kNN is like asking your friends which toys are closest in looks to the new one. 6. Naive Bayes: - Think of a detective trying to solve a mystery. Naive Bayes is like the detective making guesses based on the probability of certain clues leading to the culprit. 7. K-Means Clustering: - Imagine sorting your toys into different groups based on their similarities, like putting all the cars in one group and all the dolls in another. 8. Hierarchical Clustering: - Picture organizing your toys into groups, and then those groups into bigger groups. It's like creating a family tree for your toys based on their similarities. 9. Principal Component Analysis (PCA): - Suppose you have many different measurements for your toys, and PCA helps you find the most important ones to understand and compare them easily. 10. Neural Networks (Deep Learning): - Think of a robot brain with lots of interconnected parts. Each part helps the robot understand different aspects of things, like recognizing shapes or colors. 11. Gradient Boosting algorithms: - Imagine you are trying to reach the top of a hill, and each time you take a step, you learn from the mistakes of the previous step to get closer to the summit. XGBoost and LightGBM are like smart ways of learning from those steps. Share with credits: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D ENJOY LEARNING 👍👍

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🔍 Real-World Data Analyst Tasks & How to Solve Them As a Data Analyst, your job isn’t just about writing SQL queries or making dashboards—it’s about solving business problems using data. Let’s explore some common real-world tasks and how you can handle them like a pro! 📌 Task 1: Cleaning Messy Data Before analyzing data, you need to remove duplicates, handle missing values, and standardize formats. ✅ Solution (Using Pandas in Python):

import pandas as pd  
df = pd.read_csv('sales_data.csv')  
df.drop_duplicates(inplace=True)  # Remove duplicate rows  
df.fillna(0, inplace=True)  # Fill missing values with 0  
print(df.head())

💡 Tip: Always check for inconsistent spellings and incorrect date formats! 📌 Task 2: Analyzing Sales Trends A company wants to know which months have the highest sales. ✅ Solution (Using SQL):

SELECT MONTH(SaleDate) AS Month, SUM(Quantity * Price) AS Total_Revenue  
FROM Sales  
GROUP BY MONTH(SaleDate)  
ORDER BY Total_Revenue DESC;

💡 Tip: Try adding YEAR(SaleDate) to compare yearly trends! 📌 Task 3: Creating a Business Dashboard Your manager asks you to create a dashboard showing revenue by region, top-selling products, and monthly growth. ✅ Solution (Using Power BI / Tableau): 👉 Add KPI Cards to show total sales & profit 👉 Use a Line Chart for monthly trends 👉 Create a Bar Chart for top-selling products 👉 Use Filters/Slicers for better interactivity 💡 Tip: Keep your dashboards clean, interactive, and easy to interpret! Like this post for more content like this ♥️ Share with credits: https://t.me/sqlspecialist Hope it helps :)