Modernization of financial analysis via a comprehensive analytical platform.​

  • Practice
  • Team

1 cloud architect, 1 back-end developer, 1 Power BI front-end developer, 1 project manager​

  • Technical environment
of data
  • Extract data from 4 on-prems SQL databases, an Azure SQL database, and from an online CRM via a REST API
  • Make them available to a few selected people in the business units (internal customers) in SQL format or via Power BI
  • That data be updated at the frequencies required by internal customers: daily or hourly according to business topics + every 2 minutes during office hours for a very specific operational need
  • Architecture involving Microsoft Fabric for data management and analysis, including lakehouses and SQL endpoints for analysis.
  • Temporary adaptation of the architecture pending updates to Microsoft Fabric to simplify direct data extraction.
  • Use of Azure Data Factory for on-premises data extraction and Azure Data Lake for temporary storage.
  • Easily accessible production reports (Power BI in the browser), which update automatically and contain quality data validated by subject matter expert
  • Centralization of data required by analysts.
  • Improved data security by design: Instead of the analysts extracting data from production servers and store them as Excel files on their workstation, the data remains at all times in Fabric.
  • Improved data governance. Documentation of calculation rules and requirements via a matrix bus, Azure DevOps, and data mapping documents.