Data Warehousing is a method that is generally used to collect and handle data from various other sources to provide the business a meaningful business insight. A data warehouse is specifically created for the goals of support management decisions. The Data Warehouse has two main parts which are as follows ... Read More

The Metadata hub is used for handling the interchange and distributing of technical Metadata between decision processing products. It is designed for use primarily by technical staff during the growth and maintenance of data warehouses. There are four requirements of this hub are −A Metadata hub should provide the interchange ... Read More

A data warehouse architecture exhibits several layers of data in which data from one layer are changed from data of the lower layer. Data sources, also known as stored in open databases, form the lowest layer. They include structured data saved in the open database system and legacy systems, or ... Read More

A bitmap filter is beneficial only if it is selective. The query optimizer decides when an optimized bitmap filter is selective enough to be helpful and to which operators the filter is used. The optimizer field the optimized bitmap filters on all departments of a star join and uses costing ... Read More

HOLAP represents Hybrid OLAP. It can manage a tradeoff between ROLAP’s scalability and MOLAP’s query implementation, some commercial OLAP servers are depended on the HOLAP method. In this case, the user determines which portion of the data to save in the MOLAP and which in the ROLAP. For example, generally, ... Read More

MOLAP represents Multidimensional OLAP. It supports tuples as the data storage unit. The MOLAP applies a dedicated n-dimensional array storage engine and OLAP middleware to handle data. Hence, OLAP queries are completed through direct addressing to the associated multidimensional views (data cubes).This structure focuses on the pre-computation of the transactional ... Read More

ROLAP represents Relational OLAP. It can save the data based on the familiar relational DBMS technology. In this method, data and the related aggregations are saved in RDBMS, and OLAP middleware is used to execute the handling and exploration of data cubes.This architecture targets the optimization of the RDBMS back ... Read More

In the multidimensional model, data are arranged into several dimensions, and each dimension includes several levels of abstraction represented by concept hierarchies. This organization supports users with the adaptability to view records from different perspectives.Several OLAP data cube operations continue to materialize these multiple views, enabling interactive querying and analysis ... Read More

A concept hierarchy represents a series of mappings from a set of low-level concepts to larger-level, more general concepts. Concept hierarchy organizes information or concepts in a hierarchical structure or a specific partial order, which are used for defining knowledge in brief, high-level methods, and creating possible mining knowledge at ... Read More

Star SchemaA star schema is a conference for organizing the records into dimension tables, fact tables, and materialized views. All of the information is stored in columns, and metadata is needed to identify the columns that function as multidimensional objects.A star schema is a relational schema where a relational schema ... Read More