The Galileo approach follows a pull rather then push approach for business reporting. Under this scheme stakeholders of the company are able to access frequent audited data and pull specific information about the company. This approach calls for more frequent reporting and more disaggregated data, and business reporting rather then the limited financial reporting. Specifically, each company will provide access to part of its database (limited access permission to audited data) and stakeholders could tap into this resource. Some of the information should be disaggregated to the extent that it allow users to view the granular data or aggregate the data based on a number of given standards, assumptions and estimates. The following section provides a description of the technology described in Figure 25.
The Galileo model has a number of layered technological components. The first lower layer components comprises of the OLTP (Online Transaction Processing System) which is layered on top of a central enterprise relational database management system. An ERP system is an example for such application that provide cross functional integration for companies. The term Enterprise Resource Planning (ERP) refers to systems that typically span the entire enterprise and address all of the enterprise's resources. In addition to being able to handle multiple currencies and languages, a key feature of ERP systems is cross-functional integration. ERP systems are based on the so-called client-server architecture that is comprised of three tiers (or layers) that segregate: 1) the user interface (Presentation Layer), 2) the application processing component (Application Layer), and 3) the database system (Database Layer). Every ERP system has one central database that is accessed by all application servers. This central database is accessed by all ERP users, regardless of which module they use.
The enterprise ERP system and the relational database provide companies with the ability to generate and use real time data. This operational data is continuously assured using continuous auditing techniques such as embedded audit modules, parallel simulation and controls tags. One the assurance is done this data is periodically migrated into the corporate data warehouse. A data warehouse is a repository storing integrated information for efficient querying and analysis. Due to its non-transaction oriented nature, data warehouse allows for efficient storage and extraction of information. Because the data warehouse is separate from the corporate operating environment it is possible to use sophisticated indexing techniques to facilitate efficient data retrieval. Using OLAP (Online Analytical Processing) it is possible to extract summarized data and to drill down to the needed level of detail.
Therefore, the next layer in the stack is the OLAP engine which allow for data aggregation and disaggregation. The OLAP engine can create cubes of data based on predefined attributes and enable detailed representation based on numerous sub-attributes and categories. An OLAP interface engine would allow unsophisticated users to use this powerful tool based on their level of permission. In other word, an authorization and authentication layer would exist on top of the OLAP engine layer to provide users with the appropriate access into the data warehouse. An access control metrics will be devised based on a need to know basis and the level of publicity of the data. Specifically, and anonymous permission will be given to any un-identified user wishing to access the least restricted form of financial information. Other forms of access controls will be assigned based on some predefined criteria[1]. The OLAP engine is going to be masked so that users will not have to interface with the underlined infrastructure. The next layer is the aggregation layer, this layer interacts with the OLAP engine assisting in defining attributes and level of aggregation of the data. The aggregation layer will comprise of but is not limited to rules and standards such as GAAP and IGAAP by which data can be aggregated and models and estimates that the company uses. Again, users will not interface directly with the aggregation layer, users will logon to a secured website and will have a number of functionalities based on there authorization level. Users will use active web pages to request for specific data. All the data items that will be displayed with be made available in XBRL format as well. Data can comprise of an entire consolidated financial statement or a breakdown of detailed information about particular account in any of the virtual entity.
