Data Analyst Interview Resources
前往频道在 Telegram
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
显示更多📈 Telegram 频道 Data Analyst Interview Resources 的分析概览
频道 Data Analyst Interview Resources (@dataanalystinterview) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 52 606 名订阅者,在 教育 类别中位列第 3 250,并在 印度 地区排名第 6 703 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 52 606 名订阅者。
根据 28 八月, 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 18,过去 24 小时变化为 -7,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 1.94%。内容发布后 24 小时内通常能获得 0.83% 的反应,占订阅者总量。
- 帖子覆盖: 每篇帖子平均可获得 1 019 次浏览,首日通常累积 435 次浏览。
- 互动与反馈: 受众积极参与,单帖平均反应数为 2。
- 主题关注点: 内容集中在 sql, row, |--, dataset, visualization 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:
“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”
凭借高频更新(最新数据采集于 29 八月, 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。
52 606
订阅者
-724 小时
-587 天
+1830 天
帖子存档
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🗄️ SQL Developer Roadmap
📂 SQL Basics (SELECT, WHERE, ORDER BY)
∟📂 Joins (INNER, LEFT, RIGHT, FULL)
∟📂 Aggregate Functions (COUNT, SUM, AVG)
∟📂 Grouping Data (GROUP BY, HAVING)
∟📂 Subqueries & Nested Queries
∟📂 Data Modification (INSERT, UPDATE, DELETE)
∟📂 Database Design (Normalization, Keys)
∟📂 Indexing & Query Optimization
∟📂 Stored Procedures & Functions
∟📂 Transactions & Locks
∟📂 Views & Triggers
∟📂 Backup & Restore
∟📂 Working with NoSQL basics (optional)
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∟✅ Apply for SQL Dev Roles
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Most Demanding Data Analytics Skills!
↳ Dive into the essential skills and tools that are shaping the future of data analytics. From SQL and Python to Tableau and PowerBI, discover which technologies are crucial for advancing your data analysis capabilities.
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Uber Business Analyst Interview: 1-3 Years Experience
SQL Queries:
1. Develop an SQL query to retrieve the third transaction for each user, including user ID, transaction amount, and date.
2. Compute the average driver rating for each city using data from the rides and ratings tables.
3. Construct an SQL query to identify users registered with Gmail addresses from the 'users' database.
4. Define database denormalization.
5. Analyze click-through conversion rates using data from the
ad_clicks and cab_bookings tables.
6. Define a self-join and provide a practical application example.
Scenario-Based Question:
1. Determine the probability that at least two of three recommended driver routes are the fastest, assuming a 70% success rate for each route.
Guesstimate Questions:
1. Estimate the number of Uber drivers operating in Delhi.
2. Estimate the daily departure volume of Uber vehicles from Bengaluru Airport.
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