Static Query is a stored parameterized procedure. It is optimized for access to a particular data warehouse.  It can never be denied that the data warehouse is one of the biggest forms of data repository. In fact since a data warehouse contains the business organizations repository of historical data every single day the volume increases...

The star schema which is sometimes called a star join schema is one of the most simple styles of a data warehouse schema. It consists of a few fact tables that reference any number of dimension tables. The facts tables hold the main data with the typically smaller dimension tables describing each individual value of a dimension. Star Schema is...

Massive Parallel Processing MPP is the shared nothing” approach of parallel computing. It is a type of computing wherein the process is being done by many CPUs working in parallel to execute a single program. One of the most significant differences between a Symmetric Multi-Processing or SMP and Massive Parallel Processing is that...

An Enterprise Data Model is a representation of single definition of data of an enterprise is and the representation is not biased on any system application. It independently defines how the data is sources stored processed or accessed physically. Enterprise Data Model gives overall picture of an industry perspective by offering an integrated blueprint...

A primary is one of the most important aspects of a database implementation and its function is mainly to make records in the database table unique to avoid redundancy. Primary keys are generally used in the design and implementation of relational database systems.  The primary key which is often called a unique key is a candidate key a key...

In Lightly Summarized Data the evaluational data is summarized by removing one or a few data characteristic from the primary key of the data focus. Any company implementing a data warehouse is investing in large amount of money in the hope of getting relevant information that will help the company come up with very sound decisions to give them...

Multi-Dimensional Database is a database which has been constructed with the multiple dimensions pre-filled in hyper dimensional cubes” of data rather than the traditional two dimensional tables of Relational Databases. It is also a database concept designed for decision support systems in which related data is stored in multidimensional...

Multiple Dimension Processing is also referred to as static data analysis because the data values do not change. The role of information in today s business environment has become so tremendous that business organizations can literally not function without it. In fact companies are spending millions of dollars just to implement an enterprise data...

Multi-Dimensional Analysis is an Informational Analysis on data which takes into account many different relationships each of which represents a dimension. For example a retail analyst may want to understand the relationships among sales by region by quarter by demographic distribution income education level gender by product. Multi-dimensional...

Data warehouse implementation although basically the similar in that is based on certain data architecture and data models also has several differences brought about the differences in hardware and software platforms which are hosting the databases. In a data warehouse specially the very large ones there are various data sources. Big companies typically...

A data warehouses has a set of processes which is called ETL standing for extract transform load. The case of a data warehouse implementation involves several databases in different data stores scattered in different nodes with the information system network. These data stores can be of different systems. For instance one data stored may be running...

Data extraction is the very first part of a popular and very integral part of a data warehousing implementation called the ETL which stands for extract transform load. This set of processes is the mechanism for a data warehouse to consolidate data coming from different database with disparate systems. Each of the disparate database powering data...

A logical data model is an important aspect in the design and implementation of a data warehouse in that the efficiency of the databases depends heavily on data models. Logical Data Model refers to the actual implementation of a conceptual module in a database. It represents normalized design of common data model which is required to support the...

Information consumers are everywhere are it has become of life that data and information have become driving forces in almost all aspects of our daily operations. With the ubiquity of the internet connection today s information consumers includes people of all ages and all walks of life and even non humans like artificial intelligence technologies...

An integrated data resource is composed of many different data sources that have been applied with several tools to overcome disparities. For instance without the aide of integration tools a business enterprise may have several database systems in each of the departments within the business organizations. These database systems may be relational...

An Executive Information System EIS as a management information system is generally designed to be emphasized with graphical display and very easy to use and appealing interfaces as this is assumed to be used for supporting and facilitating the information and decision making needs of senior executives.  EIS offer strong ad-hoc...

Four-Schema Concept Four-Schema concept consist of a physical schema a logical schema a data view schema and a business schema. The use of the four schema concept is greatly taken advantaged of the in the implementation of a service oriented business processes integration. It helps to resolve problems with 3-schema...

A data warehouse is a subject-oriented integrated time-variant non-volatile collection of data in support of management s decision making process" . As brief backgrounder a data warehouse is a rich repository of corporate data containing not just historical corporate information which is tightly integrated into the operational database...

Scientifically data architecture refers to the method of designing planning and implementing an integrated data resources which is driven by business rules and based on the real world entities activities and processes which are being represented as objects perceived by the organization. The data architecture is what provides the guide for the...

Metadata are data about data; each metadata describes an individual data content item or a collection of data which includes multiple content items. Metadata Synchronization consolidates related data from different systems and synchronizes them for easier access. Metadata are very important components of any data warehouse implementation because...