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 unstructured or semi-structured data saved in files. There are several types of success associated with data warehousing which are as follows −Economic success − The data warehouse has a specific impact on the bottom line.Political success − People like what is done. If the data warehouse is not required, it’s ... 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 rules to decide whether the plan supports the smallest estimated implementation cost.When the optimized bitmap filter is nonselective, the cost estimate is generally too high and the plan is rejected. When considering where to locate optimized bitmap filters in the plan, the optimizer views for hash join variants include a ... 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, the low-level data are saved using a relational database, while higher-level data, including aggregations, are stored in an independent MOLAP.HOLAP is a mixture of ROLAP (relational OLAP) and MOLAP (multidimensional OLAP) which are different implementations of OLAP. HOLAP enables storing elements of the data in a MOLAP store and another ... 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 information into the aggregations, which results in fast query execution performance. Particularly, MOLAP pre-computes and stores aggregated measures at each hierarchy level at load time, and stores and indexes these values for immediate retrieval.The full pre-computation needed a large amount of overhead, both in processing time and in the storage ... 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 end and supports more tools and services including data cube navigation logic. Because of the use of the RDBMS back end, the main benefit of ROLAP is scalability in managing high data volumes.These are the intermediate servers that stand in among a relational back-end server and client front-end tools. They ... 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 of the data at hand. Therefore, OLAP supports a convenient environment for interactive data analysis.Five basic OLAP commands are used to implement data retrieval from a Data warehouse are as follows −ROLL UP Command − The ROLL UP enables the user to summarise information into a higher general level in ... 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 several levels of abstraction.A conceptual hierarchy includes a set of nodes organized in a tree, where the nodes define values of an attribute known as concepts. A specific node, “ANY”, is constrained for the root of the tree. A number is created to the level of each node in a ... 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 whose design describes a multidimensional data model. The star schema is the explicit data warehouse schema. It is called a star schema because the entity-relationship diagram of this schemas reproduces a star, with points, diverge from the main table. The middle of the schema includes a large fact table, and ... Read More

The snowflake schema is a variant of the star schema model, where some dimension tables are normalized, by further dividing the records into additional tables. The developing schema graph forms a shape equivalent to a snowflake.The snowflake schema is an extension of the star schema where each point of the star breaks out into more points. It is known as the snowflake schema because the snowflake schema resembles a snowflake. Snowflaking is a method of normalizing the dimension tables in STAR schemas. When it normalizes all the dimension tables completely, the resultant structure simulates a snowflake with the fact table ... Read More

A star schema is a conference for constructing the data into dimension tables, fact tables, and materialized views. All data is saved 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 whose design defines a multidimensional data model. The star schema is the explicit data warehouse schema. It is referred to as star schema because the entity-relationship diagram of this schemas reproduces a star, with points, diverge from the main table. The middle of the schema includes a high fact table, and the star ... Read More