Resources
I really believe that learning Analytics and BI should be democratized for everyone!
Hence, here you will find datasets, case studies and business problems to practice with Excel, Power BI, SQL, Python and Generative AI
Excel Data Cleaning
Objectives:
Objective 1
Understand how real-world datasets often contain inconsistencies, missing values, and formatting issues that must be cleaned before analysis.
Objective 2
Practice using important Excel formulas and data cleaning techniques to transform raw data into a structured and analysis-ready dataset.
Objective 3
Develop the mindset of a data analyst by preparing messy operational data so it can later be used for meaningful insights, dashboards, and business analytics.
Description:
This problem is designed to help you practice one of the most important skills in Data Analytics and Business Analytics cleaning and preparing messy data. In this exercise, you will work with a large dataset of 100,000 rows exported from an ERP system that contains several inconsistencies and formatting issues. Your task is to transform this raw information into a clean and structured dataset using Excel formulas and data preparation techniques.
Skills You Will Practice:
• Cleaning and preparing messy datasets commonly found in business systems
• Applying important Excel formulas for text correction, formatting, and data transformation
• Identifying and fixing inconsistencies such as extra spaces, incorrect capitalization, and missing values
• Structuring raw operational data so it becomes ready for Data Analytics and Business Analytics
• Developing the analytical thinking required before creating reports or Power BI dashboards
Marketing Dashboard
Objectives:
Objective 1
Understand how customers move through different stages of a marketing funnel, from awareness to purchase.
Objective 2
Analyze drop-off points between funnel stages to identify where potential customers are being lost.
Objective 3
Evaluate the effectiveness of different marketing channels such as web, store, and catalog in converting customers.
Description:
In this project, you will step into the role of a marketing analyst responsible for understanding how customers move through a company’s marketing funnel.
Businesses invest heavily in campaigns, website traffic, and promotions, but not every customer who shows interest ends up making a purchase.
Your task is to analyze how customers progress through different funnel stages such as website visits, campaign engagement, and final purchases. Using Excel and Power BI, you will identify where potential customers drop off, compare how different channels perform, and uncover insights that could help the marketing team improve conversions.
This project helps you understand how data analytics and business analytics are used to evaluate marketing performance and optimize customer journeys.
Skills You Will Practice:
• Understanding the structure of a marketing funnel and customer journey analytics
• Using Excel formulas and calculations to create funnel stage metrics
• Analyzing conversion rates and drop-off points across funnel stages
• Building Power BI dashboards to visualize funnel performance and channel effectiveness
• Translating data findings into clear business insights for marketing decision-making