Data Analyst Interview Resources
Join our telegram channel to learn how data analysis can reveal fascinating patterns, trends, and stories hidden within the numbers! 📊 For ads & suggestions: @love_data
Ko'proq ko'rsatish📈 Telegram kanali Data Analyst Interview Resources analitikasi
Data Analyst Interview Resources (@dataanalystinterview) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 52 629 obunachidan iborat bo'lib, Taʼlim toifasida 3 268-o'rinni va Hindiston mintaqasida 6 686-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 52 629 obunachiga ega bo‘ldi.
01 Sentabr, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 34 ga, so‘nggi 24 soatda esa 3 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 1.84% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 0.82% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 967 marta ko‘riladi; birinchi sutkada odatda 430 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 2 ta reaksiya keladi.
- Tematik yo‘nalishlar: Kontent sql, row, |--, dataset, visualization kabi asosiy mavzularga jamlangan.
📝 Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“Join our telegram channel to learn how data analysis can reveal fascinating patterns, trends, and stories hidden within the numbers! 📊
For ads & suggestions: @love_data”
Yuqori yangilanish chastotasi (oxirgi ma’lumot 02 Sentabr, 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.
NULLs, constraints
🧠 Interview Tip: Be able to explain Primary vs Foreign Key.
2️⃣ Basic Queries
🔹 SELECT, FROM, WHERE, ORDER BY, LIMIT
🧠 Practice: Filter and sort data by multiple columns.
3️⃣ Joins – Very Frequently Asked!
🔹 INNER, LEFT, RIGHT, FULL OUTER JOIN
🧠 Interview Tip: Explain the difference with examples.
🧪 Practice: Write queries using joins across 2–3 tables.
4️⃣ Aggregations & GROUP BY
🔹 COUNT, SUM, AVG, MIN, MAX, HAVING
🧠 Common Question: Total sales per category where total > X.
5️⃣ Window Functions
🔹 ROW_NUMBER(), RANK(), DENSE_RANK(), LAG(), LEAD()
🧠 Interview Favorite: Top N per group, previous row comparison.
6️⃣ Subqueries & CTEs
🔹 Write queries inside WHERE, FROM, and using WITH
🧠 Use Case: Filtering on aggregated data, simplifying logic.
7️⃣ CASE Statements
🔹 Add logic directly in SELECT
🧠 Example: Categorize users based on spend or activity.
8️⃣ Data Cleaning & Transformation
🔹 Handle NULLs, format dates, string manipulation (TRIM, SUBSTRING)
🧠 Real-world Task: Clean user input data.
9️⃣ Query Optimization Basics
🔹 Understand indexing, query plan, performance tips
🧠 Interview Tip: Difference between WHERE and HAVING.
🔟 Real-World Scenarios
🧠 Must Practice:
• Sales funnel
• Retention cohort
• Churn rate
• Revenue by channel
• Daily active users
🧪 Practice Platforms
• LeetCode (Easy–Hard SQL)
• StrataScratch (Real business cases)
• Mode Analytics (SQL + Visualization)
• HackerRank SQL (MCQs + Coding)
💼 Final Tip:
Explain why your query works, not just what it does. Speak your logic clearly.
💬 Tap ❤️ for more!