This project focuses on identifying key performance indicators (KPIs) for PwC's demo business, particularly in the areas of Call Centre Trends, Customer Retention, and Diversity & Inclusion. The project follows a structured approach starting from data cleaning and transformation, followed by the formulation of business insights questions, application of DAX (Data Analysis Expressions) calculations using relevant logic and functions, and finally, data visualization to present the identified KPIs using various chart types such as Cards, Bar Charts, Line Charts, Gauge Charts, etc.
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Data Cleaning and Transformation: Initially, the raw data was cleaned and transformed to prepare it for analysis. This involved tasks such as handling missing values, data formatting, and standardization.
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Business Insights Questions: A set of business insights questions were collected to guide the analysis and identify the most relevant KPIs for the business areas under consideration.
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DAX Calculations: DAX calculations were applied to the cleaned data to derive meaningful insights and calculate the required KPIs. This involved using appropriate DAX functions and logical expressions to perform calculations based on the business requirements.
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Data Visualization: The final step involved creating visualizations to represent the identified KPIs in an easy-to-understand format. Various chart types such as Cards, Bar Charts, Line Charts, Gauge Charts, etc., were used to effectively communicate the insights derived from the data analysis.
data/: Contains the raw and cleaned datasets used in the analysis.scripts/: Includes scripts for data cleaning, DAX calculations, and data visualization.reports/: Contains reports summarizing the analysis findings and insights.visualizations/: Stores the visualizations generated during the data visualization phase.
To get started with the project, follow these steps:
- Clone the repository to your local machine.
- Navigate to the
scripts/directory and run the data cleaning script to preprocess the raw data. - Execute the DAX calculation scripts to derive the required KPIs.
- Run the data visualization scripts to generate visualizations of the KPIs.
- Explore the reports in the
reports/directory to understand the analysis findings in detail.
The project requires the following dependencies:
- Python 3.x
- Power BI Desktop or any other data visualization tool supporting DAX calculations
- Libraries: pandas, numpy, matplotlib, seaborn (for data cleaning, analysis, and visualization)
Contributions to the project are welcome! If you find any issues or have suggestions for improvements, feel free to open an issue or submit a pull request.
This project is licensed under the MIT License.