Pre-Built Data Warehouse on Azure SQL Server
Business Driver
The Medical Appliances & Equipment Manufacturer analytics team used SAP Hana and BODS as an integration service to load their data warehouse. Customer wanted to make the move to cloud infrastructure to reduce the overhead costs and were looking at suitable cloud solutions that would replace their existing data platform and integration platform. This replacement would require a rebuild of their ETL adaptors for their analytical models in Finance, COPA, SCM, and CRM Models.
Selection Process
Medical Appliances & Equipment Manufacturer selected the Microsoft Azure SQL Server as a cloud database solution and SSIS as their Data Integration tool. Medical Appliances & Equipment Manufacturer selected KPI Partners because of their proven track record and past experiences implementing KPI Cloud Analytics for finance, SCM, and CRM in the Finance & Health Industry.
What KPI Delivered
KPI Partners analyzed the existing EDW and proposed a reference architecture including KPI Cloud Analytics for Finance, SCM, CRM, and COPA. With partitions and column-store indexing, the KPI Cloud Analytics solution supports incremental data loads, adhering to audit and logging processes, every 15 minutes to provide near real-time data for Finance users supporting EOQ operations.
With aggressive product release dates, the validation and regression test scenarios were required to be thoroughly planned, completed on time, and include Medical Appliances & Equipment Manufacturer's stringent testing criteria to support a successful product launch. A wide range of business reporting is now supported through Tableau, allowing the business user to visualize, amongst others, the Balance Sheet and intercompany transactions.
Business Benefits
- Pre-built Accelerators for faster deployment
- Single Source of Truth for all data
- Data Governance & Security Rigor
- Scalable and sustainable Analytics Platform
- Incorporate EDW Best practices in the Finance models
- Open to advanced data scientists for Ad-hoc Querying
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