We continue on our discussion on advanced topics of data warehouse. We look at financial data warehouse next.Financials are a great starting point for the data warehouse. They usually involve a small amount of data and are close to the business. However the financial data is very application oriented and not corporate oriented so there are some transformations involved. The basis for the warehouse data could be a different time period, currency unit or even classifications than that from the application. Therefore the financial analyst needs more information about the architecture than the others.
Similar to financial data, the warehouse's system of record such as for account balance must be constantly maintained. A system of record is the definitive source for a data. For example if a bank maintains account balances for customers, there should be one place where the balance is accurately reflected. Everything else is copy of this data. As data is passed to the data warehouse environment, data changes from current value to historical data. As such a system of record for historical data is created and this is then used for all kind of DSS processing.
The Corporate Information Factory that the data warehouse evolved into had two prominent features - the virtual operational data store and the addition of unstructured data. The VODS was a feature that allowed organizations to access data on the fly without building an infrastructure This meant that corporate communications could now be combined with corporate transactions to paint a more complete picture.
Archival data was another feature added to the CIF. Data would now be transferred from data warehouse to nearline storage using Cross media stroage manager (CMSM) and then retired to archival.
Another feature that was added to CIF was the unstructured visualization technology which was the equivalent for business intelligence for quantitative data.
The Government Information Factory was created along the same lines as the CIF but there are differences. These are the need for widespread integration and sharing beyond the agency, the need to accommodate data for very long periods of time and the need for security from the outset of design.
The emerging trends on the CIF now include directions involving Analytics, ERP/SAP business intelligence, unstructured business intelligence, the capturing and management of massive volumes of data
Similar to financial data, the warehouse's system of record such as for account balance must be constantly maintained. A system of record is the definitive source for a data. For example if a bank maintains account balances for customers, there should be one place where the balance is accurately reflected. Everything else is copy of this data. As data is passed to the data warehouse environment, data changes from current value to historical data. As such a system of record for historical data is created and this is then used for all kind of DSS processing.
The Corporate Information Factory that the data warehouse evolved into had two prominent features - the virtual operational data store and the addition of unstructured data. The VODS was a feature that allowed organizations to access data on the fly without building an infrastructure This meant that corporate communications could now be combined with corporate transactions to paint a more complete picture.
Archival data was another feature added to the CIF. Data would now be transferred from data warehouse to nearline storage using Cross media stroage manager (CMSM) and then retired to archival.
Another feature that was added to CIF was the unstructured visualization technology which was the equivalent for business intelligence for quantitative data.
The Government Information Factory was created along the same lines as the CIF but there are differences. These are the need for widespread integration and sharing beyond the agency, the need to accommodate data for very long periods of time and the need for security from the outset of design.
The emerging trends on the CIF now include directions involving Analytics, ERP/SAP business intelligence, unstructured business intelligence, the capturing and management of massive volumes of data
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