This project focuses on analyzing mortgage trading data using Power BI, applying various data analytics techniques to uncover insights into market trends, trading behaviors, and financial performance. Throughout the project, I have leveraged a combination of skills, including data modeling, data transformation with Power Query, and advanced DAX calculations, to structure and interpret the data effectively.
The dataset includes detailed information on mortgage transactions, interest rates, trading volumes, and other financial metrics. I started by cleaning and transforming the raw data, ensuring it was suitable for analysis. Using Power BI’s visualization tools, I created interactive dashboards that highlight key trends such as market performance over time, regional trading activities, and patterns in interest rate fluctuations.
Some of the most important insights derived from the analysis include:
- Identification of regions with the highest trading volumes and their impact on overall market performance.
- Analysis of how interest rate changes correlate with fluctuations in trading activity.
- A breakdown of high-performing mortgage products based on trading metrics.
The insights from this analysis can be used to guide decision-making in mortgage trading strategies, offering stakeholders a clear view of market dynamics and areas of opportunity.
Get the data frames here!
