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 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 the client’s existing data setup and single truth of data, as well as requirements for data quality, data scalability, data performance and availability needs for informational analysis, data security, data capture (flow), data preparation, data publication, data analytics, and non-functional requirements.
On completion of the requirements and exploration process, we provided the services and data population constructs that 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 into appropriate business schemas
- Data publication layer, which pushed the data to the existing data warehouse and other reporting structures as determined by requirements gathering and discovery exercises.
The project was successfully implemented over a five-month timeframe.