Dolman Bateman
A BI Case Study for Doleman Bateman
Sector
Financial
Services
Power BI Reports
Team Size
2
Engagement
Starting up & Scaling up
Introduction
Doleman Bateman is a well-established accounting firm based in Australia, renowned for its financial expertise and client-centric approach. With a diverse portfolio of clients, the firm sought to gain deeper insights into the financial performance of their clients and improve their decision-making processes.
Business Objective
- Insightful Analysis: The primary objective was to gain actionable insights into the Sales and financial data of their various clients.
- Enhanced Decision-Making: Doleman Bateman aimed to enhance their decision-making processes by having a comprehensive view of their clients’ financial health.
- Financial Performance Analysis: The firm sought to improve its ability to assess and analyze the financial performance of their clients accurately.
Project Scope
- Data Analysis and Visualization: The project involved the analysis and visualization of Sales & Financial data, allowing clients to better understand their financial standing.
- Data Integration: Data was integrated from multiple sources, including Xero, XMP, Excel, and CSV files, to provide a holistic view of financial information.
- KPI-Driven Reports: Custom KPI-driven reports were created to provide clients with specific, actionable insights.
- BI Tool Implementation: Power BI was chosen as the BI tool for ongoing monitoring and analysis.
Data Collection and Integration
- Data from diverse sources, such as Xero, XMP, Excel, and CSV files, was collected.
- Python scripts were used for data extraction, transformation, and loading (ETL) processes.
- Centralized data storage and management were achieved through AWS RDS.
Key Performance Indicators (KPIs)
- Invoice vs Budget: Tracking and comparing actual invoices to budgeted amounts.
- Sales vs Budget: Evaluating actual sales performance against budgeted figures.
- Budget YTD (Year-to-Date): Monitoring budget performance throughout the year.
- Custom KPIs: Tailored KPIs were developed to address specific client needs, including expense tracking and profitability ratios.
BI Tools and Technologies
- Power BI: This tool was chosen for its robust data visualization capabilities and user-friendly dashboards.
- ETL Process: Python scripts were employed for ETL, ensuring data accuracy and consistency.
- Data Storage: AWS RDS served as a secure and scalable platform for data storage.
- SQL: SQL was used for data manipulation and retrieval, enabling efficient data analysis.
Data Analysis and Insights
- Interactive dashboards were created in Power BI, allowing clients to visualize and explore their financial data.
- Trends, anomalies, and patterns in financial data were identified, providing clients with actionable insights.
- Drill-down capabilities enabled clients to delve into detailed data for deeper analysis.
- Data-driven recommendations were provided to improve financial performance.
Challenges and Solutions:
- Data Quality: Data inconsistencies and errors were addressed through rigorous data cleaning and validation scripts.
- Data Integration: Custom ETL processes were developed to harmonize data from different sources.
- Security and Compliance: Ensuring data security and compliance with relevant regulations was a top priority.
- Client-specific Needs: Reports and KPIs were tailored to meet individual client requirements, ensuring relevancy and usefulness.
Conclusion
- The project successfully empowered Doleman Bateman to gain deeper insights into their clients’ Sales & Financial data.
- Power BI dashboards gave clients the tools they needed to make informed financial decisions.
- Custom KPIs improved financial performance tracking and provided valuable benchmarks.
- The use of AWS RDS and Python streamlined data management and integration.
- Overall, the Business Intelligence solution enhanced Doleman Bateman’s ability to provide valuable financial services to their clients, improving client satisfaction and fostering business growth.