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لا تقع ضحية للمخادعين! تيليمتريو يكتشف ويُميّز هذه القنوات 👉 إذا كنت تريد رؤية العلامة، اشترك

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

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

الذهاب إلى القناة على Telegram

Data Analysis Useful Resources #dataanalysis #dataanalysisbooks #sqlbooks #pythonbooks #tableau #powerbi #datavisualization For promotions: @coderfun

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📈 نظرة تحليلية على قناة تيليجرام Data Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources

تُعد قناة Data Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources (@learndataanalysis) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 53 305 مشتركاً، محتلاً المرتبة 3 304 في فئة التعليم والمرتبة 6 419 في منطقة الهند.

📊 مؤشرات الجمهور والحراك

منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 53 305 مشتركاً.

بحسب آخر البيانات بتاريخ 03 نوفمبر, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار 23، وفي آخر 24 ساعة بمقدار -1، مع بقاء الوصول العام مرتفعاً.

  • حالة التحقق: غير موثّقة
  • معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 7.12‎%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 1.16‎% من ردود الفعل نسبةً إلى إجمالي المشتركين.
  • وصول المنشورات: يحصل كل منشور على متوسط 0 مشاهدة. وخلال اليوم الأول يجمع عادةً 616 مشاهدة.
  • التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 0.
  • الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل analyst, |--, excel, visualization, analytic.

📝 الوصف وسياسة المحتوى

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“Data Analysis Useful Resources #dataanalysis #dataanalysisbooks #sqlbooks #pythonbooks #tableau #powerbi #datavisualization For promotions: @coderfun”

بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 04 نوفمبر, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التعليم.

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Hey guys 👋 I was working on something big from last few days. Finally, I have curated best 80+ top-notch Data Analytics Resources 👇👇 https://topmate.io/analyst/861634 If you go on purchasing these books, it will cost you more than 15000 but I kept the minimal cost for everyone's benefit. I hope these resources will help you in data analytics journey. I will add more resources here in the future without any additional cost. All the best for your career ❤️

✔️📚A beginner's roadmap for learning SQL: 🔺Understand Basics: Learn what SQL is and its purpose in managing relational databases. Understand basic database concepts like tables, rows, columns, and relationships. 🔺Learn SQL Syntax: Familiarize yourself with SQL syntax for common commands like SELECT, INSERT, UPDATE, DELETE. Understand clauses like WHERE, ORDER BY, GROUP BY, and JOIN. 🔺Setup a Database: Install a relational database management system (RDBMS) like MySQL, SQLite, or PostgreSQL. Practice creating databases, tables, and inserting data. 🔺Retrieve Data (SELECT): Learn to retrieve data from a database using SELECT statements. Practice filtering data using WHERE clause and sorting using ORDER BY. 🔺Modify Data (INSERT, UPDATE, DELETE): Understand how to insert new records, update existing ones, and delete data. Be cautious with DELETE to avoid unintentional data loss. 🔺Working with Functions: Explore SQL functions like COUNT, AVG, SUM, MAX, MIN for data analysis. Understand string functions, date functions, and mathematical functions. 🔺Data Filtering and Sorting: Learn advanced filtering techniques using AND, OR, and IN operators. Practice sorting data using multiple columns. 🔺Table Relationships (JOIN): Understand the concept of joining tables to retrieve data from multiple tables. Learn about INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN. 🔺Grouping and Aggregation: Explore GROUP BY clause to group data based on specific columns. Understand aggregate functions for summarizing data (SUM, AVG, COUNT). 🔺Subqueries: Learn to use subqueries to perform complex queries. Understand how to use subqueries in SELECT, WHERE, and FROM clauses. 🔺Indexes and Optimization: Gain knowledge about indexes and their role in optimizing queries. Understand how to optimize SQL queries for better performance. 🔺Transactions and ACID Properties: Learn about transactions and the ACID properties (Atomicity, Consistency, Isolation, Durability). Understand how to use transactions to maintain data integrity. 🔺Normalization: Understand the basics of database normalization to design efficient databases. Learn about 1NF, 2NF, 3NF, and BCNF. 🔺Backup and Recovery: Understand the importance of database backups. Learn how to perform backups and recovery operations. 🔺Practice and Projects: Apply your knowledge through hands-on projects. Practice on platforms like LeetCode, HackerRank, or build your own small database-driven projects. 👀👍Remember to practice regularly and build real-world projects to reinforce your learning. Happy Learning 🥳 📚

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🥳🚀When delving into data analytics and initiating your SQL journey, prioritize mastering the fundamental concepts that address the majority of problems before delving into other topics. 👉🏻 Basic Aggregation function: 1️⃣ AVG 2️⃣ COUNT 3️⃣ SUM 4️⃣ MIN 5️⃣ MAX 👉🏻 JOINS 1️⃣ Left 2️⃣ Inner 3️⃣ Self (Important, Practice questions on self join) 👉🏻 Windows Function (Important) 1️⃣ Learn how partitioning works 2️⃣ Learn the different use cases where Ranking/Numbering Functions are used? ( ROW_NUMBER,RANK, DENSE_RANK, NTILE) 3️⃣ Use Cases of LEAD & LAG functions 4️⃣ Use cases of Aggregate window functions 👉🏻 GROUP BY 👉🏻 WHERE vs HAVING 👉🏻 CASE STATEMENT 👉🏻 UNION vs Union ALL 👉🏻 LOGICAL OPERATORS Other Commonly used functions: 👉🏻 IFNULL 👉🏻 COALESCE 👉🏻 ROUND 👉🏻 Working with Date Functions 1️⃣ EXTRACTING YEAR/MONTH/WEEK/DAY 2️⃣ Calculating date differences 👉🏻CTE 👉🏻Views & Triggers (optional) Here is an amazing resources to learn & practice SQL: https://bit.ly/3FxxKPz Hope it helps in your SQL learning 📚

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Best practices for writing SQL queries: Join for more: https://t.me/learndataanalysis 1- Write SQL keywords in capital letters. 2- Use table aliases with columns when you are joining multiple tables. 3- Never use select *, always mention list of columns in select clause. 4- Add useful comments wherever you write complex logic. Avoid too many comments. 5- Use joins instead of subqueries when possible for better performance. 6- Create CTEs instead of multiple sub queries , it will make your query easy to read. 7- Join tables using JOIN keywords instead of writing join condition in where clause for better readability. 8- Never use order by in sub queries , It will unnecessary increase runtime. 9- If you know there are no duplicates in 2 tables, use UNION ALL instead of UNION for better performance. SQL Basics: https://t.me/sqlanalyst/105

Here are some Excel shortcuts that are commonly used by data analysts: 1. Ctrl + C: Copy 2. Ctrl + V: Paste 3. Ctrl + X: Cut 4. Ctrl + Z: Undo 5. Ctrl + Y: Redo 6. Ctrl + S: Save 7. Ctrl + F: Find 8. Ctrl + H: Replace 9. Ctrl + Arrow Keys: Navigate to the edge of data 10. Ctrl + Shift + Arrow Keys: Select data range 11. Ctrl + Home: Go to cell A1 12. Ctrl + End: Go to last cell with data 13. Ctrl + Shift + L: Toggle filters 14. Alt + ; : Select visible cells only 15. F2: Edit active cell 16. Ctrl + Shift + Enter: Enter an array formula 17. Ctrl + D: Fill down 18. Ctrl + R: Fill right 19. Ctrl + 1: Format cells dialog box 20. Ctrl + Shift + 1, 2, 3, etc.: Apply different number formats These shortcuts can significantly increase your efficiency when working with Excel as a data analyst. One of the very important tool that a data analyst must be aware of is Excel

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My journey as a data analyst so far: https://www.linkedin.com/posts/sql-analysts_today-i-decided-to-share-my-journey-in-data-activity-7169341885914853376-GWnd?utm_source=share&utm_medium=member_android Feel free to comment your experience as well. I usually don't share my personal journey online but sometimes even small things like this help others. I hope you guys can relate with me ❤️

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Learn like IITians 🚀 Attend Introduction to SQL for Data Analysis Workshop Today! Register now : https://digikull.com/eventdetails?data=0&sessionId=4 Date : 1st March | 8:00 PM to 10:00 PM Eligibility: College Students and Working Professionals! 1. Understand the fundamentals of SQL. 2. Introduction to SQL queries for data analysis. 3. Hands-on exercises and real-world examples. 4. Q&A session with the expert. 👉 Hurry Up! Limited Seats Available