Data warehousing approach Data warehousing is an integral part of the kBOS knowledge management services. Advanced data warehousing techniques are used to extract and disseminate information on the performance of the company processes. This information can then be used by decision makers to design operational improvements or strategic changes. The kBOS Platform Data Warehouse delivers precise information in order to support decisions The typical process information provided are: · where the process bottlenecks are; employee productivity and utilisation rates; process or task duration; process or a task costs. The kBOS Data Warehouse Module The kBOS Data Warehouse Module consists of three components: a) the relational database (Snowflake Schema) b) the multidimensional database (Cube) c) the presentation layer (Pivot table & Chart) The ETL (Extract Transform Load) Process is used to: a) extract and collect the data from the transactional database (Core kBOS Database), b) transform / renormalize the data in a comprehensive way and c) load/populate (inserts only new data) the snowflake structured database with the data. The ETL process runs on a scheduled basis when the system is idle and there is no user activity. The next and final step after the population of the relational database is the incremental update of the multidimensional database (Cube). Both of the above mentioned processes run either in two separated transactions or in one transaction ensuring recovery in case of a system failure. This is achieved with the features provided by the Data Transformation Services of the Microsoft SQL Server. Also the kBOS DTS services use the SQL’s Meta Data Services in order to provide important system information to database administrators. The common kBOS Data Warehouse Model can be extended to accommodate specific enterprise informational needs The extensions can be undertaken by any developer who understands the data warehousing basic techniques.
Data warehousing is an integral part of the kBOS knowledge management services. Advanced data warehousing techniques are used to extract and disseminate information on the performance of the company processes. This information can then be used by decision makers to design operational improvements or strategic changes.
The kBOS Platform Data Warehouse delivers precise information in order to support decisions The typical process information provided are:
· where the process bottlenecks are;
employee productivity and utilisation rates;
process or task duration;
process or a task costs.
The kBOS Data Warehouse Module
The kBOS Data Warehouse Module consists of three components:
a) the relational database (Snowflake Schema)
b) the multidimensional database (Cube)
c) the presentation layer (Pivot table & Chart)
The ETL (Extract Transform Load) Process is used to:
a) extract and collect the data from the transactional database (Core kBOS Database),
b) transform / renormalize the data in a comprehensive way and
c) load/populate (inserts only new data) the snowflake structured database with the data.
The ETL process runs on a scheduled basis when the system is idle and there is no user activity.
The next and final step after the population of the relational database is the incremental update of the multidimensional database (Cube).
Both of the above mentioned processes run either in two separated transactions or in one transaction ensuring recovery in case of a system failure. This is achieved with the features provided by the Data Transformation Services of the Microsoft SQL Server. Also the kBOS DTS services use the SQL’s Meta Data Services in order to provide important system information to database administrators.
The common kBOS Data Warehouse Model can be extended to accommodate specific enterprise informational needs The extensions can be undertaken by any developer who understands the data warehousing basic techniques.