Data Analysis And Visualization – Python, Excel, Power Bi, Tableau
Course Overview:
“Data Analysis and Visualization – Python, Excel, Power BI, Tableau” is a comprehensive course that provides learners with the essential skills and knowledge to perform data analysis and visualization using a combination of Python, Excel, Business Intelligence (BI) tools, and Tableau. The course is divided into several sections, each focusing on a specific tool or technology, including Python, Excel, Power BI, and Tableau.
Who Needs This Course:
This course is suitable for a diverse range of individuals, including:
Data Analysts and Data Scientists: Data analysts and data scientists who want to enhance their data analysis capabilities and leverage multiple tools for comprehensive data exploration and visualization will find this course valuable. It covers both Python, a versatile programming language for data analysis, and popular BI and visualization tools like Excel, Power BI, and Tableau.
Business Professionals: Business professionals who work with data and want to gain insights from their datasets can benefit from this course. They will learn how to use Excel, Power BI, and Tableau to analyze and visualize data, enabling them to make data-driven decisions and effectively communicate findings to stakeholders.
Students and Aspiring Data Professionals: Students pursuing a career in data analysis, business intelligence, or data visualization can take this course to acquire a solid foundation in multiple data analysis tools. The course covers Python, Excel, Power BI, and Tableau, providing a well-rounded skill set that is highly sought after in the industry.
Managers and Decision-Makers: Managers and decision-makers who rely on data for strategic decision-making will benefit from this course. They will learn how to leverage various tools to analyze, visualize, and present data in a meaningful way, empowering them to gain insights and drive informed decisions.
How Learners Will Benefit:
Comprehensive Data Analysis Skill Set: By completing this course, learners will acquire a comprehensive skill set in data analysis using Python, Excel, Power BI, and Tableau. They will gain proficiency in performing tasks such as data cleaning, data manipulation, data visualization, and storytelling.
Python for Data Analysis: Learners will be introduced to Python, one of the most popular programming languages for data analysis. They will learn how to work with Jupyter Notebook, explore and manipulate data using Pandas, and perform basic data cleaning and visualization tasks.
Excel for Data Analysis: The course covers data analysis with Excel, including using Power Pivot and Power Query to connect to data sources, clean and transform data, create data models, and generate visualizations such as pivot tables and charts.
Power BI for Data Analysis: Participants will learn how to use Power BI Desktop and Power BI Service to connect to data sources, clean and transform data, create interactive visualizations, and publish reports to share with others.
Tableau for Data Analysis: The course includes an introduction to Tableau, a popular data visualization tool. Learners will learn how to connect to data sources, clean and prepare data, explore Tableau’s interface, and create visualizations and interactive dashboards.
Data Cleaning and Transformation: Learners will gain practical skills in data cleaning and transformation techniques using various tools. They will learn how to handle inconsistent fields, split text into multiple columns, change data types, remove/reorder columns, and perform other data cleaning tasks.
Data Visualization and Storytelling: The course emphasizes data visualization techniques and storytelling principles. Learners will explore different visualization types and learn how to create impactful visualizations, arrange fields in visualizations, and present data effectively to convey insights.
Practical Hands-on Experience: Throughout the course, learners will have the opportunity to apply their knowledge and skills through hands-on exercises and projects. This practical experience will help solidify their understanding and prepare them for real-world data analysis tasks.
By completing the “Data Analysis and Visualization – Python, Excel, Power BI, Tableau” course, learners will gain a strong foundation in data analysis using multiple tools, enabling them to tackle diverse data challenges, uncover valuable insights, and communicate findings with clarity and impact.
SECTION 1: INTRODUCTION TO PYTHON
SECTION 2: DATA ANALYSIS WITH PYTHON
SECTION 3: DATA ANALYSIS WITH POWER BI
-
20What Is Power Bi
-
21What Is Power Bi Desktop
-
22Installing Power Bi Desktop
-
23Power Bi Desktop Tour
-
24Power Bi Overview Part 1
-
25Power Bi Overview Part 2
-
26Power Bi Overview Part 3
-
27Components Of Power Bi
-
28Building Blocks Of Power Bi
-
29Exploring Power Bi Desktop Interface
-
30Exploring Power Bi Service
-
31Power Bi Apps
-
32Connecting To Web Data
-
33Clean And Transform Data Part 1
-
34Clean And Transform Data Part 2
-
35Combining Data Sources
-
36Creating Visualization Part 1
-
37Creating Visualization Part 2
-
38Publishing Reports To Power Bi Service
-
39Importing And Transporting Data From Access DB File
-
40Changing Locale
-
41Connecting To MS Access DB File
-
42Power Query Editor And Queries
-
43Creating And Managing Query Groups
-
44Renaming Queries
-
45Splitting Columns
-
46Changing Data Types
-
47Removing And Reordering Columns
-
48Duplicating And Adding Columns
-
49Creating Conditional Columns
-
50Connecting To Files In Folder
-
51Appending Queries
-
52Merge Queries
-
53Query Dependency View
-
54Transform Less Structured Data Part 1
-
55Transform Less Structured Data Part 2
-
56Creating Tables
-
57Query Parameters
SECTION 4: DATA ANALYSIS WITH EXCEL
-
58Office 365 Setup (Optional)
-
59Activating Office 365 (Optional)
-
60Logging Into Office 365 (Optional)
-
61What Is Power Pivot
-
62Office Versions Of Power Pivot
-
63Enable Power Pivot In Excel
-
64What Is Power Query
-
65Connecting To A Data Source
-
66Preparing Query
-
67Cleansing Data
-
68Enhancing Query
-
69Creating A Data Model
-
70Building Data Relationships
-
71Create Lookups With DAX
-
72Analyse Data With Pivot Tables
-
73Analyse Data With Pivot Charts
-
74Refresh Source Data
-
75Update Queries
-
76Create New Reports
SECTION 5: DATA ANALYSIS WITH TABLEAU
-
77What Is Tableau
-
78Tableau Data Sources
-
79Tableau File Types
-
80Tableau Help Menu
-
81Connect To A Data Source
-
82Join Related Data Sources
-
83Join Data Sources With Inconsistent Field
-
84Data Cleaning
-
85Exploring Tableau Interface
-
86Reorder Fields In Visualization
-
87Change Summary
-
88Split Text Into Multiple Columns
-
89Presenting Data Using Stories