Data Analysis with (Power Bi, Tableau, Excel)

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Course Description

Data Analysis with Power BI, Tableau, and Excel is a comprehensive course designed to equip participants with the skills necessary to analyze and visualize data effectively using three powerful tools: Power BI, Tableau, and Excel. Through a combination of lectures, hands-on exercises, and real-world case studies, participants will learn how to explore, transform, and present data to derive actionable insights and drive informed decision-making.

Who is this course for?

  • Business analysts, data analysts, and data scientists seeking to enhance their data analysis skills.
  • Professionals working in marketing, finance, operations, or any field that requires data-driven decision-making.
  • Students pursuing degrees or certifications in business analytics, data science, or related disciplines.

Course Goals

  • Master the fundamentals of data analysis.
  • Gain proficiency in using Power BI, Tableau, and Excel for data visualization and analysis.
  • Learn to clean, transform, and prepare data for analysis.
  • Develop skills in creating interactive dashboards and reports.
  • Understand advanced data analysis techniques such as predictive modeling and statistical analysis.

Prerequisites

  • Basic understanding of data concepts and terminology.
  • Familiarity with spreadsheet software (e.g., Microsoft Excel) is advantageous but not mandatory.
  • No prior experience with Power BI or Tableau is required, but familiarity with any data visualization tool would be beneficial.

Introduction to Data Analysis

  1. Overview of data analysis process
  2. Importance of data-driven decision-making
  3. Introduction to Power BI, Tableau, and Excel for data analysis

Data Import and Preparation

  1. Importing data from various sources (Excel, CSV, databases)
  2. Data cleaning and transformation techniques
  3. Data modeling and structuring for analysis

Data Visualization Fundamentals

  1. Principles of effective data visualization
  2. Creating basic charts and graphs in Power BI, Tableau, and Excel
  3. Customizing visualizations to convey insights

Advanced Visualization Techniques

  1. Interactive dashboards and reports
  2. Drill-down and filtering capabilities
  3. Geographic and time-series visualizations

Data Analysis and Exploration

  1. Performing exploratory data analysis (EDA)
  2. Using calculated fields and measures for advanced analytics
  3. Identifying trends, patterns, and outliers in data

Advanced Analytics Features

  1. Forecasting and predictive analytics
  2. Statistical analysis using Power BI, Tableau, and Excel
  3. Integration with R and Python for advanced analytics

Data Storytelling and Communication

  1. Crafting narratives with data
  2. Communicating insights effectively to stakeholders
  3. Presenting findings through compelling visualizations and reports

Practical Projects and Case Studies

  1. Analyzing real-world datasets to extract actionable insights
  2. Designing interactive dashboards and reports to visualize findings
  3. Presenting findings and recommendations based on data analysis

Final Project

  1. Apply acquired knowledge and skills to analyze a complex dataset and derive meaningful insights.
  2. Design and present a comprehensive data analysis project using Power BI, Tableau, or Excel.
  • Comprehensive coverage of data analysis techniques using industry-standard tools: Power BI, Tableau, and Excel.
  • Hands-on learning approach with practical exercises and real-world projects to reinforce theoretical concepts.
  • Emphasis on both data visualization and analytics, enabling participants to derive actionable insights from data.
  • Exploration of advanced features such as forecasting, predictive analytics, and integration with programming languages like R and Python.
  • Focus on effective communication of data-driven insights through storytelling and compelling visualizations.
  • Suitable for individuals at all skill levels, from beginners to experienced professionals looking to enhance their data analysis capabilities.
  • Practical projects and case studies offer opportunities to apply learned concepts to real-world scenarios and datasets.
  • Final project allows participants to demonstrate their proficiency by designing and presenting a comprehensive data analysis project.

About this Course

  • Duration 4 Weeks
  • Certificate on Completion
  • Level Beginner
  • Price UGX 400,000 370,000

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