Data Marts serve as the “system of record” for decision making and information retrieval purposes of a Company that provides easy and powerful access to data. Its architecture consists of below components:
Internal Data Source / Operational Databases; Information that is procured, reported and consolidated within your organization, for example: purchase orders from sales, transactions from accounting, and leads from marketing or information from CRM software.
External Data Sources: any information obtained from a source outside of your organization, for example: information collected through census or surveys.
The metadata database is the only permanent database within DataMart architecture. This database holds all of the configurations & metadata to build and connect everything together. (i.e. configuration information, connection strings, client specific KPIs and attributes etc.).
Within a DataMart, the staging database has a short life cycle. It is a relational database built to extracted raw data from the source applications; however is ripped down once this data is loaded and populated in the DataMart/OLAP Cube using an ETL Tool.
ETL = Extract – Transform – Load
OLAP DATAMART / REPORTING:
- Integration Layer: integrates the unrelated data sets by transforming the data from the staging layer and storing this transformed data in an operational data store (ODS) database.
- The integrated data is then loaded into the DataMart relational database/OLAP Cube.
- Each step within the extraction, transformation and load process will include error handling to ensure that errors do not make it down to the data Mart.
The OLAP DataMart is made up of the relational database (Data Mart) and the OLAP Cube. OLAP Online Analytical Processing is the analyses of business data for the release of business insight.
Similar to the staging database; the relational database is specifically created and loaded with the subset of data. The OLAP cube is built and processed; and uses its in-built reporting tools to provide enhanced analytics and value add data to the organization.