Online Analytic Processing is the capability to store and manage the data in a way, so that it can be effectively used to generate actionable information. You are aware from the Business Intelligence Architecture, OLAP sits between the Data Warehouse and End-user tools. OLAP is explained in detail in OLAP vs. Data Warehouse
OLAP makes Business Intelligence happen, broadly by enabling the following:
- Transforming the data into multi-dimensional cubes
- Summarized pre-aggregated and derived data
- Strong query management
- Multitude of calculation and modeling functions
A data-warehouse could be having data in various formats like dimensional (with a high degree of de-normalization) OR highly relational (like 3rd normal form). As a separate note- We have covered the entire data-warehouse chapter on the basis of dimensional modeling based storage. Most of the concepts in the data-warehouse chapter remain the same irrespective of the kind of storage and data-modeling one needs to do. The detail differential between OLAP vs. Data Warehouse is given in OLAP Layer
OLAP provides the building blocks to enable analysis (like rich functions, multi-dimensional models, analysis types..). Mostly the end-user tools (like business modeling tools, Data mining tools, performance reporting tools..), which sit on top of the OLAP to provide rich user Business Intelligence interface. OLAP and Data warehouse work in conjunction to provide overall data-access for the end-user tools. You may like to refer to BI Architecture Scenarios to get a better back-ground. There are different way to store the data in OLAP+ Data-warehouse combination. While you can refer to OLAP Architectures in BI Architecture, here is the brief:
- MOLAP: OLAP storing the data in the multi-dimensional mode. To put it in a simplistic manner, there is one array for one combination of dimensions and associated measures. In this storage method there is no connect between the MOLAP database and data-warehouse database for query purpose. It means that a user cannot drill down from MOLAP summary data to the transaction level data of data-warehouse.
- ROLAP: OLAP storing the data in relational form in dimensional model. This is a de-normalized form in relational table structure. ROLAP database of OLAP server can be linked to the Data-warehouse database.
- HOLAP: The aggregate data is stored in the multi-dimensional model in the OLAP database and the transactional level data is stored in the relational form in the data-warehouse database. There is a linkage between the summary MOLAP database of OLAP and relational transactional database of Data-warehouse. This gives you the best of both the worlds.
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