Wavicle Case Study
Global Steel Manufacturer
We were engaged to improve the thoroughness, timeliness and accuracy of reporting across the client organization. The reporting at an enterprise level was not uniform; information was being largely gathered from source systems and the previous data warehouse through manual efforts, which were mapped to common data definitions for analysis and decision support; this process was time consuming, prone to errors and did not fully meet the client’s current business needs.
We gathered data on client’s existing data setup, single Truth of Data, Data Quality Requirements, Data Scalability Requirements, Data Performance and Availability Needs for Informational Analysis Requirements, Data Security Requirements, Data Capture (Flow) Requirements, Data Preparation Requirements, Data Publication Requirements, Data Analytic Requirements, and Non-Functional Requirements.
On completion of the requirements and exploration process, we provided the services and data population constructs which made efficient and effective informational use of the client’s transactional data, computing and personnel resources. We performed Technical Design and Development tasks and produced their outcomes, addressing three BI architectural layers, namely:
- Data Capture Layer, which acquired data from transaction sources
- Data Preparation Layer, which conformed, standardized, cleansed and integrated captured data in to appropriate business schemas
- Data Publication Layer, which pushed the data to existing data warehouse and other reporting structures as determined in requirements gathering and discovery exercises.
The project was successfully implemented over a 5 month timeframe.