The Quadrant Data Model Approach
Quadrant adopts a common approach to building enterprise wide data warehouses and specific capital adequacy and compliance reporting solutions such as our B2 or SAB2 for Basel II reporting solutions. This approach recognises that capital adequacy and compliance reporting, such as those required under Basel II, as well as anti-money laundering, customer profitability and risk pricing applications amongst others are in practice uses of enterprise wide data. They are in practice all enterprise wide business intelligence (BI) applications.
Central to our approach is the Quadrant Financial Services Enterprise Data Model. This is a comprehensive model which comes pre-packaged with knowledge across a broad range of financial sectors including retail banking, credit cards, mortgages, lending, mutual funds, investment banking and insurance. The data model is designed for the analytic environment, rather than for building operational transaction systems. It is equally suited to enterprise spanning or departmental queries. It provides the basis for building enterprise data provisioning systems. Such systems can be implemented in easily managed phases. The model is easily understood by business analysts, providing organisations the capability to add their own reporting requirements. We regularly update the model t reflect changing market requirements.
The Qadrant approach recognises that data mapping and quality are key to any successful BI solution. We provide a standardised ETL (Exact, Transfer, Load) process for loading data into the data model from operational systems.
Organisations can use a range of industry standard query tools from vendors such as Microstrategy, Business Objects, Microsoft and others to access and query the data model. Quadrant’s EPS (enterprise Presentation Server), which provides an SOA presentation layer, is used to provide real time dashboards in some of our products such as B2 and SAB2.
The benefits of the Quadrant approach include:
- Reduced implementation time
- Faster ROI
- Reduced risk
- Better quality information (“One version of the Truth”)
- High performance for BI applications
- Lower application development and maintenance costs
