What is Data Mart Consolidation? The process of merging two or more data marts into one or integrating one or more data marts into an Enterprise Data Warehouse.
All the key components of a data mart system, its data model, data integration process and the reporting process would have at least some of the objects getting eliminated or merged through the consolidation process.
Why Data Mart Consolidation? Many organizations have grown with departmental marts and these have many common processes and data which get redundantly replicated among them. As well BI systems with functional overlap would exist when an organization keeps expanding through acquisition.
All organizations will be in a phase of defining or progressing with an Enterprise Data Warehouse to enable wider reach of corporate data. As well a shared service or a competency based model is very commonly found in large installations for ease of administration of the Data Warehouse components like database, data integration tool, data quality tool or a reporting tool, to ensure common standard across the environment and as well save on the cost of the infrastructure. In a way consolidation in an environment becomes an ongoing process.
Signs for Data Mart Consolidation, following are the indicators which characterizes the need for data mart consolidation
- Users pull data from two systems and integrate them in Excel
- Users have to go through different security mechanism in each system to access data
- Users are able to generate almost similar report from two different systems
- Users report discrepancy in data that is shared between systems
- Same data is made available to different users at different times
- Existence of loops and redundant data flow in the data integration process between systems
- Existence of additional copy of data and related synchronization processes
- Existence of multiple independent servers for data integration and reporting
- Existence of multiple data integration and reporting products
Benefits of Data mart Consolidation
- Optimal infrastructure usage by consolidating servers to maximize system performance
- Save disk space by eliminating unwanted data copies
- Easier system maintenance with integrated impact analysis
- Integrated system security and user profiles
- Common metadata definitions across systems
- Common process frameworks related to error handling, process control, auditing etc
- Availability of reusable components
- Effective software license usage by eliminating unwanted data base, data integration and reporting product instances
- Standardization of technology platform and eliminating multiple skill needs
- Reducing the Data Integration window time and making data available before time to the users
- Enabling integrated cross-functional data analysis