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 39 494 名订阅者,在 教育 类别中位列第 4 752,并在 印度 地区排名第 10 399 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 39 494 名订阅者。
根据 10 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 198,过去 24 小时变化为 3,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 2.80%。内容发布后 24 小时内通常能获得 1.00% 的反应,占订阅者总量。
- 帖子覆盖: 每篇帖子平均可获得 1 107 次浏览,首日通常累积 393 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 11 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。
SELECT, FROM, WHERE, etc., to perform operations on the data.
- SQL keywords are not case-sensitive, but it's common to write them in uppercase (e.g., SELECT, FROM).
3. SQL Data Types
Databases store data in different formats. The most common data types are:
- INT (Integer): For whole numbers.
- VARCHAR(n) or TEXT: For storing text data.
- DATE: For dates.
- DECIMAL: For precise decimal values, often used in financial calculations.
4. Basic SQL Queries
Here are some fundamental SQL operations:
- SELECT Statement: Used to retrieve data from a database.
SELECT column1, column2 FROM table_name;
- WHERE Clause: Filters data based on conditions.
SELECT * FROM table_name WHERE condition;
- ORDER BY: Sorts data in ascending (ASC) or descending (DESC) order.
SELECT column1, column2 FROM table_name ORDER BY column1 ASC;
- LIMIT: Limits the number of rows returned.
SELECT * FROM table_name LIMIT 5;
5. Filtering Data with WHERE Clause
The WHERE clause helps you filter data based on a condition:
SELECT * FROM employees WHERE salary > 50000;
You can use comparison operators like:
- =: Equal to
- >: Greater than
- <: Less than
- LIKE: For pattern matching
6. Aggregating Data
SQL provides functions to summarize or aggregate data:
- COUNT(): Counts the number of rows.
SELECT COUNT(*) FROM table_name;
- SUM(): Adds up values in a column.
SELECT SUM(salary) FROM employees;
- AVG(): Calculates the average value.
SELECT AVG(salary) FROM employees;
- GROUP BY: Groups rows that have the same values into summary rows.
SELECT department, AVG(salary) FROM employees GROUP BY department;
7. Joins in SQL
Joins combine data from two or more tables:
- INNER JOIN: Retrieves records with matching values in both tables.
SELECT employees.name, departments.department
FROM employees
INNER JOIN departments
ON employees.department_id = departments.id;
- LEFT JOIN: Retrieves all records from the left table and matched records from the right table.
SELECT employees.name, departments.department
FROM employees
LEFT JOIN departments
ON employees.department_id = departments.id;
8. Inserting Data
To add new data to a table, you use the INSERT INTO statement:
INSERT INTO employees (name, position, salary) VALUES ('John Doe', 'Analyst', 60000);
9. Updating Data
You can update existing data in a table using the UPDATE statement:
UPDATE employees SET salary = 65000 WHERE name = 'John Doe';
10. Deleting Data
To remove data from a table, use the DELETE statement:
DELETE FROM employees WHERE name = 'John Doe';
Here you can find essential SQL Interview Resources👇
https://t.me/DataSimplifier
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