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Complete Excel Topics for Data Analysts 😄👇

1. Introduction to Excel:
- Basic spreadsheet navigation
- Understanding cells, rows, and columns

2. Data Entry and Formatting:
- Entering and formatting data
- Cell styles and formatting options

3. Formulas and Functions:
- Basic arithmetic functions
- SUM, AVERAGE, COUNT functions

4. Data Cleaning and Validation:
- Removing duplicates
- Data validation techniques

5. Sorting and Filtering:
- Sorting data
- Using filters for data analysis

6. Charts and Graphs:
- Creating basic charts (bar, line, pie)
- Customizing and formatting charts

7. PivotTables and PivotCharts:
- Creating PivotTables
- Analyzing data with PivotCharts

8. Advanced Formulas:
- VLOOKUP, HLOOKUP, INDEX-MATCH
- IF statements for conditional logic

9. Data Analysis with What-If Analysis:
- Goal Seek
- Scenario Manager and Data Tables

10. Advanced Charting Techniques:
- Combination charts
- Dynamic charts with named ranges

11. Power Query:
- Importing and transforming data with Power Query

12. Data Visualization with Power BI:
- Connecting Excel to Power BI
- Creating interactive dashboards

13. Macros and Automation:
- Recording and running macros
- Automation with VBA (Visual Basic for Applications)

14. Advanced Data Analysis:
- Regression analysis
- Data forecasting with Excel

15. Collaboration and Sharing:
- Excel sharing options
- Collaborative editing and comments

16. Excel Shortcuts and Productivity Tips:
- Time-saving keyboard shortcuts
- Productivity tips for efficient work

17. Data Import and Export:
- Importing and exporting data to/from Excel

18. Data Security and Protection:
- Password protection
- Worksheet and workbook security

19. Excel Add-Ins:
- Using and installing Excel add-ins for extended functionality

20. Mastering Excel for Data Analysis:
- Comprehensive project or case study integrating various Excel skills

Since Excel is another essential skill for data analysts, I have decided to teach each topic daily in this channel for free. Like this post if you want me to continue this Excel series 👍♥️

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3.32K views17:17

SQL INTERVIEW PREPARATION PART-1 👇👇

What is the difference between WHERE& HAVING CLAUSE in SQL?

The WHERE and HAVING clauses in SQL are used to filter results, but they serve different purposes.

1. WHERE Clause:
- Used with the SELECT, UPDATE, and DELETE statements.
- Filters rows before the grouping or aggregation.
- Specifies conditions for selecting individual rows from the tables.
- Example: SELECT * FROM employees WHERE salary > 50000;

2. HAVING Clause:
- Used with the SELECT statement.
- Filters rows after the grouping has occurred, typically when using aggregate functions like SUM, COUNT, etc.
- Specifies conditions for filtering the results of aggregate functions.
- Example: SELECT department, AVG(salary) as avg_salary FROM employees GROUP BY department HAVING AVG(salary) > 60000;

In summary, WHERE is used for filtering rows before any grouping or aggregation, while HAVING is used for filtering results after grouping has taken place, specifically with aggregate functions.

Hope it helps :)

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3.55K views17:17

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Glad to see the amazing response for Excel Learning Series 😄❤️

Let's start with the first topic today: Introduction to Excel.

1. Basic Spreadsheet Navigation: In Excel, you navigate through the spreadsheet using the mouse or keyboard. You move between cells, rows, and columns to input, edit, or review data. Understanding how to efficiently move around the spreadsheet is fundamental for working effectively in Excel.

2. Understanding Cells, Rows, and Columns: Cells are the basic building blocks of Excel. They are the boxes where you enter data, perform calculations, or display results. Rows run horizontally, and columns run vertically. Each cell is identified by a unique combination of its column letter and row number (e.g., A1, B2, C3). Understanding the structure of cells, rows, and columns is essential for organizing and analyzing data in Excel.

Stay tuned for the next topics ☺️

Hope it helps :)

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3.83K viewsedited 20:34

CODING HACKING DEVELOPERS COLLEGE

Complete SQL Topics for Data Analysts 😄👇

1. Introduction to SQL:
- Basic syntax and structure
- Understanding databases and tables

2. Querying Data:
- SELECT statement
- Filtering data using WHERE clause
- Sorting data with ORDER BY

3. Joins:
- INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN
- Combining data from multiple tables

4. Aggregation Functions:
- GROUP BY
- Aggregate functions like COUNT, SUM, AVG, MAX, MIN

5. Subqueries:
- Using subqueries in SELECT, WHERE, and HAVING clauses

6. Data Modification:
- INSERT, UPDATE, DELETE statements
- Transactions and Rollback

7. Data Types and Constraints:
- Understanding various data types (e.g., INT, VARCHAR)
- Using constraints (e.g., PRIMARY KEY, FOREIGN KEY)

8. Indexes:
- Creating and managing indexes for performance optimization

9. Views:
- Creating and using views for simplified querying

10. Stored Procedures and Functions:
- Writing and executing stored procedures
- Creating and using functions

11. Normalization:
- Understanding database normalization concepts

12. Data Import and Export:
- Importing and exporting data using SQL

13. Window Functions:
- ROW_NUMBER(), RANK(), DENSE_RANK(), and others

14. Advanced Filtering:
- Using CASE statements for conditional logic

15. Advanced Join Techniques:
- Self-joins and other advanced join scenarios

16. Analytical Functions:
- LAG(), LEAD(), OVER() for advanced analytics

17. Working with Dates and Times:
- Date and time functions and formatting

18. Performance Tuning:
- Query optimization strategies

19. Security:
- Understanding SQL injection and best practices for security

20. Handling NULL Values:
- Dealing with NULL values in queries

Ensure to strengthen your SQL skills.

Hope it helps :)

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4.55K viewsedited 19:54

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⌨️ Method chaining, cascading, or the "Fluent API".

This style of programming involves having methods of a class return the object they operate on in order to allow a subsequent method call.

This is used to chain mutations of an instance or can also be used creating copies for immutable objects.

This is not the most common style of programming, but it does have some niche uses, which we explore in this video.

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4.15K viewsedited 11:44

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I built the same app 3 times - Which Python Framework is best? Django vs Flask vs FastAPI

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