Financial Charm Bank: Florida Branch Performance Analysis – Data Anomaly Detection, Correction, and Visualization in Power BI

Overview

You have recently been hired as a business analyst for Financial Charm Bank, a large retail bank operating in the United States. The bank’s headquarters are located in Charlotte, North Carolina, and the bank earns most of its revenues from its operations in the East Coast and Midwest. In the Q4 review, it was observed that one of the larger branches in Florida failed to meet the earnings guidance. Senior management has tasked the business analysis team to conduct a comparative review of the three largest branches in Florida.

The vice president of business analytics has tasked you with the initial data analysis and creating a final report for stakeholders. The purpose of this analysis is as follows:

• Determine how products and services are performing at each branch location.
• Review customer traffic at the drive-up and lobby areas to ensure staff availability at each branch location.
• Prescribe optimal business outcomes by applying simple predictive algorithms.

The data team has provided you with the raw data set to conduct your initial analysis.

Prompt

In this project, you will use Power BI as a visualization tool to communicate your analysis effectively. In your final report, include the following criteria:

1. Identify and analyze any data anomalies in the data set.
1. Choose two columns and create a visualization for each column that highlights the anomalies.
1. Include a screenshot of this visual in your report.
2. Explain the impact of the identified anomalies.
1. Include appropriate screenshots from Power BI to help support your reasoning.
3. Explain whether you would include these anomalies in reporting as this data is used to drive business decisions. Justify your reasoning.
2. Based on the anomalies identified, use Excel to manually correct the data set.
1. Identify the data points you corrected. Explain your reasoning.
2. Identify the data points you did not correct. Explain your reasoning.
3. Explain which manual correction techniques you used. Explain your reasoning.
3. Using the corrected data set, update the Power BI report to assess the impact of the updated anomalies.
1. Compare the updated visualizations to those prior to correcting the data set. How do they differ? Explain your reasoning.
2. Include appropriate screenshots from Power BI to help support your reasoning.
   please submit a 5 page paper with single spacing