Data Analytics Projects - SQL, Excel, Tableau, Python & Power BI Interview Resources
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
显示更多📈 Telegram 频道 Data Analytics Projects - SQL, Excel, Tableau, Python & Power BI Interview Resources 的分析概览
频道 Data Analytics Projects - SQL, Excel, Tableau, Python & Power BI Interview Resources (@sqlproject) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 39 487 名订阅者,在 教育 类别中位列第 4 735,并在 印度 地区排名第 10 481 位。
📊 受众指标与增长动态
自 невідомо 创建以来,项目保持高速增长,吸引了 39 487 名订阅者。
根据 05 六月, 2026 的最新数据,频道保持稳定运转。过去 30 天订阅人数变化为 254,过去 24 小时变化为 18,整体触达仍然可观。
- 认证状态: 未认证
- 互动率 (ER): 平均受众互动率为 2.49%。内容发布后 24 小时内通常能获得 0.86% 的反应,占订阅者总量。
- 帖子覆盖: 每篇帖子平均可获得 982 次浏览,首日通常累积 339 次浏览。
- 互动与反馈: 受众积极参与,单帖平均反应数为 3。
- 主题关注点: 内容集中在 analytic, dataset, visualization, sql, learning 等核心主题上。
📝 描述与内容策略
作者将该频道定位为表达主观观点的平台:
“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”
凭借高频更新(最新数据采集于 06 六月, 2026),频道始终保持新鲜度与高覆盖。分析显示受众积极互动,使其成为 教育 类别中的关键影响点。
COALESCE or IS NULL checks
3️⃣ Wrong JOIN Type
• INNER instead of LEFT
• Data silently disappears
• Always ask: Do you need unmatched rows?
4️⃣ Missing JOIN Conditions
• Creates cartesian product
• Rows explode
• Always join on keys
5️⃣ Filtering After JOIN Instead of Before
• Processes more rows than needed
• Slower performance
• Filter early using WHERE or subqueries
6️⃣ Using WHERE Instead of HAVING
• WHERE filters rows
• HAVING filters groups
• Aggregates fail without HAVING
7️⃣ Not Using Indexes
• Full table scans
• Slow dashboards
• Index columns used in JOIN, WHERE, ORDER BY
8️⃣ Relying on ORDER BY in Subqueries
• Order not guaranteed
• Results change
• Use ORDER BY only in final query
9️⃣ Mixing Data Types
• Implicit conversions
• Index not used
• Match column data types
🔟 No Query Validation
• Results look right but are wrong
• Always cross-check counts and totals
🧠 Practice Task
• Rewrite one query
• Remove SELECT *
• Add proper JOIN
• Handle NULLs
• Compare result count
SQL Resources: https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v
❤️ Double Tap For MoreSELECT MAX(salary)
FROM employees
WHERE salary < (SELECT MAX(salary) FROM employees);
2️⃣ List employees who earn more than the average salary.
SELECT name, salary
FROM employees
WHERE salary > (SELECT AVG(salary) FROM employees);
3️⃣ Show department-wise highest paid employee.
SELECT department, name, salary
FROM (
SELECT *,
RANK() OVER (PARTITION BY department ORDER BY salary DESC) AS rnk
FROM employees
) AS ranked
WHERE rnk = 1;
4️⃣ Display total sales made by each employee in 2023.
SELECT emp_id, SUM(amount) AS total_sales
FROM sales
WHERE YEAR(sale_date) = 2023
GROUP BY emp_id;
5️⃣ Retrieve products with price above average in their category.
SELECT p.name, p.category, p.price
FROM products p
WHERE price > (
SELECT AVG(price)
FROM products
WHERE category = p.category
);
6️⃣ Identify duplicate emails in the users table.
SELECT email, COUNT(*)
FROM users
GROUP BY email
HAVING COUNT(*) > 1;
7️⃣ Rank customers based on total purchase amount.
SELECT customer_id,
SUM(amount) AS total_spent,
RANK() OVER (ORDER BY SUM(amount) DESC) AS rank
FROM orders
GROUP BY customer_id;
💬 Double Tap ❤️ For More!
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