The Data Analyst’s Toolkit: Excel, SQL, Python, Power BI

سرفصل های دوره

Data Mastery for the Modern Analyst: Excel, SQL, Python, and Power BI Techniques

1. Introduction to Data Analysis

1. Introduction

2. Course Introduction.html

3. Data Analysis Overview

4. Roles in Data Analysis

5. Tasks of a Data Analyst

6. Importance of Data-Driven Decision Making.html

2. Excel Fundamentals

1. Introduction to Excel

2. Opening a new workbook

3. Entering data in Excel

4. Basic data entry in Excel

5. Entering data with autofil

6. Entering date

7. Entering time

8. Undo and redo changes

9. Adding comments

10. Adding a title to worksheet

11. Saving your work

12. Introduction to Excel Functions and Formulas

13. Using formulas for arithmetic tasks

14. Re-using formulas

15. Calculating YTD Profits

16. Calculating percentage change

17. Relative and absolute reference

18. Using Rank Function

19. STD Function

20. Small and Large Functions

21. Median Function

22. Count and Counta Functions

23. Exploring fonts

24. Adjusting column width and row height

25. Using alignment

26. Designing borders

27. Formatting Numbers

28. Conditional formatting

29. Creating tables

30. Inserting shapes

3. Data Analysis & Visualization with Excel

1. What is Power Query

2.1 EV sales (King county).zip

2. Connecting to a data source

3. Please Read.html

4.1 Prep.xlsx

4. Preparing the query

5.1 Cleansing.xlsx

5. Cleaning the data

6.1 Enhance.xlsx

6. Enhancing the query

7. What is Power Pivot

8. How to enable Power Pivot

9.1 PrepPP.xlsx

9. Create a data model

10.1 AddData.xlsx

10. Importing data and creating relationships

11.1 Lookups.xlsx

11. Creating lookups with DAX

12. Analyze data with Pivot Tables

13.1 Charts.xlsx

13. Analyze data with Pivot Charts

14.1 Refresh.xlsx

14. Refreshing source data

15.1 Update.xlsx

15. Updating queries

16. Creating new reports

4. SQL and MySQL Fundamentals

1. Introduction to SQL

2. Introduction to MySQL

3. MySQL Installation (Windows)

4. MySQL Installation (Mac)

5. What is MySQL Workbench

6. Basic database concepts

7. What is a Schema

8. Database Schema

9. MySQL Data Types

10. Joining Multiple Tables with INNER Join

11. Joining Multiple Tables with LEFT Join

12. Joining Multiple Tables with RIGHT Join

13. Joining Multiple Tables with SELF Join

14. Removing duplicates from query results

15. Group data by combing rows

16. Filter grouped results

17. Sort query results

18. Filtering rows of data

19. Introduction to aggregate functions

20. Using COUNT Aggregate Function

21. Using SUM Aggregate Function

22. Using AVG Aggregate Function

23. Using MIN Aggregate Function

24. Using MAX Aggregate Function

25. What are Subqueries

26. Using Nested Subqueries

5. Python Fundamental

1. What is Python

2. Installing Python on Windows

3. Installing Python on Macs

4. What is Jupyter Notebook

5. Installing Jupyter Notebook

6. Running Jupyter Notebook Server

7. Some Jupyter Notebook Commands

8. Jupyter Notebook Components

9. The Notebook Dashboard

10. The Notebook user interface

11. Creating a new notebook

12. Python expressions

13. Python statements

14. Python Comments

15. Python data types

16. Casting data types

17. Python Variables

18. Python List

19. Python Tuple

20. Python dictionaries

21. Python Operators

22. Python Conditional statements

23. Python Loops

24. Python Functions

6. Data Analysis and Visualization with Python and SQL

1. Create a virtual environment on Windows

2. Create a virtual environment on Macs

3. Activate a virtual environment on Windows

4. Activate a virtual environment on Macs

5. Upgrade Pip

6. Install Visual Studio Code

7. Required Python Packages.html

8. Installing Python Packages

9. Import packages into a Python file

10. The Sakilla Database

11. Establishing a connection to the database

12. Write a Python function to execute SQL queries

13. Asking relevant questions about the data.html

14. What are the most popular film categories rented by customers

15. How does the average rental duration vary across film categories

16. Which actors are featured in the most rented films.html

17. Are there any seasonal trends in the rental volume.html

18. What is the average rental cost by film category.html

19. How does the revenue contribution from different film categories compare.html

20. Are there any correlations between film length and rental frequency.html

21.1 scripts.zip

21. Download the Python files.html

7. Introduction to Power BI

1. What is Power BI

2. What is Power BI Desktop

3. Install Power BI Desktop

4. Explore Power BI Desktop Interface

5. Microsoft 365 Setup

6. Getting started with Microsoft 365

7. Create a new user account in Microsoft 365

8. Components of Power BI

9. Getting data into Power BI Desktop

8. Data Analysis and Visualization with Power BI

1.1 Financial+Sample.xlsx

1. Connect to data source

2. Transform the data

3. Model the data

4. Visualize the data

5. Publish report to Power BI Service

6. Build a dashboard

7. Collaborate and share

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تولید کننده: Udemy-Training