The management of our client organization wanted to receive assurances on the accuracy of the financial statements and reports generated by their Enterprise Resources & Planning (ERP) software application. We were tasked with generating various financial statements and reports by independently querying the ERP’s databases using our data analysis toolset. The financial statements of interest included – The Balance Sheet, Profit & Loss Statements, Revenue and Cost of Sales Reports, Accounts Payable and Accounts Receivable reports.

The key was to generate these reports and statements completely independently of the ERP by re-constructing the data held in various journals and tables on the software databases. Furthermore, this reports were to be published in real-time on dynamic visual dashboards that could be accessed by the company management on demand.

Using Arbutus Analyzer and Python, we built a robust script that would query more than 50 different database tables, rebuild all the statements and reports by performing analysis on the datasets, and finally publish the results to a data repository where PowerBI’s ™ On-Premise Gateway would fetch the analyzed data and publish onto visual dashboards.

For this assignment, we took advantage of Arbutus’ seamless integration with the Python programming language and built a number of scripts and procedures on Python. The Python scripts enabled our team to perform complex analysis and data manipulation in a quick and efficient manner. The dataset was then returned to Arbutus Analyzer for further analysis and ‘polish’ before being sent to a data repository to be fetched by Microsoft’s PowerBI™. The entire process is self contained in a single script that can be scheduled or run on-demand.