• Decentralized information: Various financial data sources over 10 years, led to decentralized information.
• Outdated data: Dealing with outdated, duplicate, and inaccurate financial data which added complexities and inefficiencies in their process.
• Decision making: Struggling to make business-critical decisions due to the lack of information.​

We addressed the challenges faced by a finance team with Google Cloud Platform (GCP).

The project started as a proof of concept on Azure Data Lake Storage (ADLS) and was later migrated to Google Cloud Platform (GCP).
​A second phase focused on migrating a large volume of transaction data to GCP, as the development team started using GCP as the primary source of financial information.​

Given that the project was facing delays and errors with data transfer using IDocs from SAP applications, our team created dashboards on Big Query for real-time error detection and developed a user interface to interact with and reprocess failed IDOCs to ensure data integrity.
Also, an ETL process was established to ingest data from different sources into various data marts, including SAP S4/Hana and Tax Hub. ​

Finally, to provide actionable insights and facilitate decision-making, we created detailed markdown reports. These reports offered clear visibility into resource tagging and usage patterns, empowering stakeholders to make informed decisions about resource optimization and cost management.