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Data Analytics

Data Analytics

Kanalga Telegramโ€™da oโ€˜tish

Dive into the world of Data Analytics โ€“ uncover insights, explore trends, and master data-driven decision making. Admin: @HusseinSheikho || @Hussein_Sheikho

Ko'proq ko'rsatish

๐Ÿ“ˆ Telegram kanali Data Analytics analitikasi

Data Analytics (@dataanalyticsx) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 28 972 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 4 734-o'rinni va Rossiya mintaqasida 22 757-o'rinni egallagan.

๐Ÿ“Š Auditoriya koโ€˜rsatkichlari va dinamika

ะฝะตะฒั–ะดะพะผะพ sanasidan buyon loyiha tez oโ€˜sib, 28 972 obunachiga ega boโ€˜ldi.

14 Iyun, 2026 dagi oxirgi maโ€™lumotlarga koโ€˜ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 507 ga, soโ€˜nggi 24 soatda esa 8 ga oโ€˜zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya oโ€˜rtacha 3.66% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.27% ini tashkil etuvchi reaksiyalarni toโ€˜playdi.
  • Post qamrovi: Har bir post oโ€˜rtacha 1 061 marta koโ€˜riladi; birinchi sutkada odatda 369 ta koโ€˜rish yigโ€˜iladi.
  • Reaksiyalar va oโ€˜zaro taโ€™sir: Auditoriya faol: har bir postga oโ€˜rtacha 2 ta reaksiya keladi.
  • Tematik yoโ€˜nalishlar: Kontent sellerflash, buybox, buyer, chaos, effortless kabi asosiy mavzularga jamlangan.

๐Ÿ“ Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida taโ€™riflaydi:
โ€œDive into the world of Data Analytics โ€“ uncover insights, explore trends, and master data-driven decision making. Admin: @HusseinSheikho || @Hussein_Sheikhoโ€

Yuqori yangilanish chastotasi (oxirgi maโ€™lumot 15 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli boโ€˜lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim taโ€™sir nuqtasiga aylantirishini koโ€˜rsatadi.

28 972
Obunachilar
+824 soatlar
+837 kunlar
+50730 kunlar
Postlar arxiv
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SQL interview.pdf4.57 MB

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This channels is for Programmers, Coders, Software Engineers. 0๏ธโƒฃ Python 1๏ธโƒฃ Data Science 2๏ธโƒฃ Machine Learning 3๏ธโƒฃ Data Visua
This channels is for Programmers, Coders, Software Engineers. 0๏ธโƒฃ Python 1๏ธโƒฃ Data Science 2๏ธโƒฃ Machine Learning 3๏ธโƒฃ Data Visualization 4๏ธโƒฃ Artificial Intelligence 5๏ธโƒฃ Data Analysis 6๏ธโƒฃ Statistics 7๏ธโƒฃ Deep Learning 8๏ธโƒฃ programming Languages โœ… https://t.me/addlist/8_rRW2scgfRhOTc0 โœ… https://t.me/Codeprogrammer

#๐—ฆ๐—ค๐—Ÿ ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฒ๐˜„ ๐—–๐—ต๐—ฒ๐—ฎ๐˜๐˜€๐—ต๐—ฒ๐—ฒ๐˜ โ†’ ๐—–๐—ฟ๐—ฎ๐—ฐ๐—ธ ๐—”๐—ป๐˜† ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฒ๐˜„ ๐—ช๐—ถ๐˜๐—ต ๐—ง๐—ต๐—ฒ๐˜€๐—ฒ ๐—–๐—ผ๐—ป๐—ฐ๐—ฒ๐—ฝ๐˜๐˜€ โžœ
#๐—ฆ๐—ค๐—Ÿ ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฒ๐˜„ ๐—–๐—ต๐—ฒ๐—ฎ๐˜๐˜€๐—ต๐—ฒ๐—ฒ๐˜ โ†’ ๐—–๐—ฟ๐—ฎ๐—ฐ๐—ธ ๐—”๐—ป๐˜† ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฒ๐˜„ ๐—ช๐—ถ๐˜๐—ต ๐—ง๐—ต๐—ฒ๐˜€๐—ฒ ๐—–๐—ผ๐—ป๐—ฐ๐—ฒ๐—ฝ๐˜๐˜€ โžœ ๐Ÿญ. ๐—ฆ๐—ค๐—Ÿ ๐—๐—ผ๐—ถ๐—ป๐˜€ โ†’ Combine data from multiple tables ๐Ÿก† INNER JOIN โ†’ Returns matching records from both tables ๐Ÿก† LEFT JOIN โ†’ Returns all records from the left table + matches from the right ๐Ÿก† RIGHT JOIN โ†’ Returns all records from the right table + matches from the left ๐Ÿก† FULL JOIN โ†’ Returns all records from both tables โžœ ๐Ÿฎ. ๐——๐—”๐—ง๐—” ๐—™๐—œ๐—Ÿ๐—ง๐—˜๐—ฅ๐—œ๐—ก๐—š โ†’ Retrieve specific records efficiently ๐Ÿก† WHERE โ†’ Filters rows before aggregation ๐Ÿก† HAVING โ†’ Filters after aggregation ๐Ÿก† BETWEEN, IN, LIKE โ†’ Advanced filtering โžœ ๐Ÿฏ. ๐—”๐—š๐—š๐—ฅ๐—˜๐—š๐—”๐—ง๐—œ๐—ข๐—ก & ๐—š๐—ฅ๐—ข๐—จ๐—ฃ๐—œ๐—ก๐—š โ†’ Summarize data ๐Ÿก† GROUP BY โ†’ Groups data based on a column ๐Ÿก† COUNT, SUM, AVG, MIN, MAX โ†’ Perform calculations โžœ ๐Ÿฐ. ๐—ฆ๐—จ๐—•๐—ค๐—จ๐—˜๐—ฅ๐—œ๐—˜๐—ฆ & ๐—–๐—ง๐—˜๐˜€ โ†’ Break complex queries ๐Ÿก† Subquery โ†’ Nested query inside another query ๐Ÿก† Common Table Expressions (CTE) โ†’ Temporary named query โžœ ๐Ÿฑ. ๐—œ๐—ก๐——๐—˜๐—ซ๐—œ๐—ก๐—š & ๐—ข๐—ฃ๐—ง๐—œ๐— ๐—œ๐—ญ๐—”๐—ง๐—œ๐—ข๐—ก โ†’ Speed up queries ๐Ÿก† Indexes โ†’ Improve search speed ๐Ÿก† EXPLAIN PLAN โ†’ Analyze query performance โžœ ๐Ÿฒ. ๐—”๐——๐—ฉ๐—”๐—ก๐—–๐—˜๐—— ๐—ฆ๐—ค๐—Ÿ ๐—ง๐—ข๐—ฃ๐—œ๐—–๐—ฆ ๐Ÿก† Window Functions โ†’ RANK, ROW_NUMBER, LEAD, LAG ๐Ÿก† Stored Procedures & Triggers โ†’ Automate tasks ๐Ÿก† Normalization & Denormalization โ†’ Optimize database design โšก๏ธ BEST DATA SCIENCE CHANNELS ON TELEGRAM ๐ŸŒŸ

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