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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

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

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📈 Telegram kanali Data Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources analitikasi

Data Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources (@learndataanalysis) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 51 872 obunachidan iborat bo'lib, Taʼlim toifasida 3 352-o'rinni va Hindiston mintaqasida 7 187-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 51 872 obunachiga ega bo‘ldi.

17 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 506 ga, so‘nggi 24 soatda esa -5 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 6.39% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.26% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 3 314 marta ko‘riladi; birinchi sutkada odatda 654 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 6 ta reaksiya keladi.
  • Tematik yo‘nalishlar: Kontent analyst, |--, excel, visualization, analytic kabi asosiy mavzularga jamlangan.

📝 Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
Data Analysis Useful Resources #dataanalysis #dataanalysisbooks #sqlbooks #pythonbooks #tableau #powerbi #datavisualization For promotions: @coderfun

Yuqori yangilanish chastotasi (oxirgi ma’lumot 18 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Taʼlim toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.

51 872
Obunachilar
-524 soatlar
+1227 kunlar
+50630 kunlar
Postlar arxiv
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50 Algorithms Every Programmer Should Know Imran Ahmad, 2023

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Microsoft Azure AI Fundamentals Certification Companion Krunal S. Trivedi, 2023

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Advanced Data Science and Analytics with Python Автор: Jesus Rogel-Salazar

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SQL vs Python SQL is great for managing and querying structured databases, especially when dealing with large datasets. It excels in tasks like filtering, sorting, and aggregating data. Python, on the other hand, is a versatile programming language used for a broader range of tasks. In the context of data, Python is powerful for data manipulation, analysis, and machine learning. It offers libraries like Pandas for data manipulation, NumPy for numerical operations, and Scikit-Learn for machine learning. In summary, SQL is essential for efficient database querying, while Python provides a more comprehensive solution for various data-related tasks, making them often used together in data-related workflows. SQL Practice Questions with Answers -> https://t.me/learndataanalysis/596 Python Roadmap for Data Analysts -> https://t.me/pythonfreebootcamp/207

Data Analysis vs Data Science Data analysis often focuses on interpreting and summarizing existing data, requiring skills like statistical analysis, SQL, and data visualization. On the other hand, data science involves a broader set of skills, including machine learning, predictive modeling, and advanced programming. In essence, data analysis is a subset of data science, with data scientists often having a more extensive toolkit for handling complex and unstructured data. Free Resources to become data analyst -> https://www.linkedin.com/posts/sql-analysts_freecertificates-dataanalysts-python-activity-7113004712412524545-Uw4k Steps to become data scientist -> https://t.me/learndataanalysis/559

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SQL Practice Questions with Answers Those who are at beginner and intermediate level in sql should try to solve all these question