You need to load your data warehouse regularly so that it can serve its purpose of facilitating business analysis.
To do this, data from one or more operational systems needs to be extracted and copied into the data warehouse. The challenge in data warehouse environments is to integrate, rearrange and consolidate large volumes of data over many systems, thereby providing a new unified information base for business intelligence.
In a normal Analytics Project Lifecycle, the BICS (Business Intelligence Cloud Services) Data Model and Analyses cannot be created until the underlying data structure, such as Data Marts or the Data Warehouse, has been modeled in the Database Cloud Service, and data has been ETL-ed into the structure.
There is a shortcut!
Once the data modelers have executed the DDL (Data Definition Language) for the Data Mart or some portion of the Data Warehouse in DBCS (Database Cloud Services), then the BICS Data Model can be created and BICS Analyses and Dashboards can also be created. The Analyses or Dashboards will not have data when they are run, but they will be ready to go once data is loaded. This will greatly cut down on the overall project implementation time.
By creating all the BICS objects once, the fields are created in DBCS, you cut down time waiting for actual data. Then, once the ETL (or ELT) loads data into Data Mart or Data Warehouse, only minor modifications may need to be made to the BICS Data Model, Analyses or Dashboards.
This requires coordination between the data modelers and the BICS developers for field changes. Whatever method is being used to track the fields of the data model, whether that is a data modeling tool or a spreadsheet, changes to the Data Mart or Data Warehouse model need to be communicated from the data modeler to the BICS developers.
It is recommended that you use collaborative methods such as Basecamp for documenting and sharing changes in the Data Mart or Data Warehouse model.
DDL – Data Definition Language
DBCS – Database Cloud Services
ETL – The process of extracting data from source systems and bringing it into the data warehouse is commonly called ETL, which stands for extraction, transformation, and loading.