Headquartered in Texas, the Customer is an international company (with about 300 employees) that is an expert in commercial and residential real estate development.
Aiming to gain deeper insight into their business, the Customer wanted to establish a comprehensive financial reporting. Instead of disparate data unsuitable for data analyzing and for making informed decisions, the Customer wanted to receive an efficient reporting tool based on the aggregate data.
In the course of the project, ScienceSoft’s BI implementation team of a data analyst, a database developer and a senior BI developer delivered the following:
- Data warehouse based on Microsoft SQL Server
- ETL using Python
- Data integration from about 40 sources
- Data cleaning and merging
- Analytical cube development with 15 dimensions and 30 measures
- Integrated financial and analytical reports and dashboards based on Power BI
Since the Customer needed a comprehensive financial analysis, ScienceSoft developed the reports to analyze the following indicators:
- Operating expenses
- Net operating income
- Net profit
- Operating cash flow
- Change in cash
- Current assets
- Fixed assets
- Current liabilities
- Long-term liabilities
To enable the Customer to get an overall picture and spot the trends, ScienceSoft also delivered dashboards and consolidated reports listed below:
- Balance Sheet
- Cash at the ends of the period
- Current assets and liabilities
- Cash flow
- Net profit
The reports show the data of both entire company and the branches. Additionally, any attribute can be chosen to filter the data (including the hierarchy of branches, accounts and dates).
At the end of the project, 17 reports (with different levels of detail) and 5 dashboards allowed the Customer to look at the aggregate financial data from any perspective and, consequently, better understand their business. Besides, the Customer was able to analyze the cash flow, spot the trends, and quickly react to a changing environment.
Technologies and Tools
Microsoft SQL Server (DWH), Python (ETL), Microsoft Power BI (Reporting)