Data mining is the process of discovering meaningful new correlations, patterns, and trends by shifting through large amounts of data stored in repositories, using pattern recognition technologies as well as statistical and mathematical techniques. It is the analysis of observational datasets to find unsuspected relationships and to summarize the data in novel ways that are both understandable and useful to the data owner.It is the procedure of selection, exploration, and modeling of high quantities of information to find regularities or relations that are at first unknown to obtain clear and beneficial results for the owner of the database. Data mining ... Read More

An OLAM server performs analytical mining in data cubes similarly to an OLAP server performs online analytical processing. An integrated OLAM and OLAP mechanism, where the OLAM and OLAP servers both accept user online queries (or commands) via a graphical user interface API and operate with the data cube in the data analysis via a cube API.A metadata directory can be used to instruct the access of the data cube. The data cube can be created by accessing and integrating multiple databases via an MDDB API and by filtering a data warehouse via a database API that can provide OLE ... Read More

Relational OLAP (ROLAP) serversThese are the intermediate servers that stand in among a relational back-end server and client front-end tools. They facilitate a relational or extended-relational DBMS to save and manage warehouse data, and OLAP middleware to provide the missing item.ROLAP servers involve optimization for each DBMS back end, implementation of aggregation navigation logic, and more tools and services. ROLAP technology tends to have higher scalability than MOLAP technology. The DSS server of Micro strategy, for instance, adopts the ROLAP techniques.ROLAP systems work generally from the data that resides in a relational database, where the base data and dimension tables ... Read More

OLAM stands for Online analytical mining. It is also known as OLAP Mining. It integrates online analytical processing with data mining and mining knowledge in multi-dimensional databases. There are several paradigms and structures of data mining systems.Various data mining tools must work on integrated, consistent, and cleaned data. This requires costly pre-processing for data cleaning, data transformation, and data integration. Thus, a data warehouse constructed by such pre-processing is a valuable source of high-quality information for both OLAP and data mining. Data mining can serve as a valuable tool for data cleaning and data integration.OLAM is particularly important for the ... Read More

Data warehouses and data marts are used in a broad area of applications. Business executives use the data in data warehouses and data marts to implement data analysis and create strategic decisions. In some firms, data warehouses are used as an integral element of a plan-execute-assess “closed-loop” feedback system for enterprise administration.Data warehouses are used widely in banking and financial services, consumer goods and retail distribution sectors, and controlled manufacturing, including demand-based production. Generally, the longer a data warehouse has been in use, the more it will have developed. This evolution takes place throughout various phases.Initially, the data warehouse is ... Read More

Data warehouses contain huge volumes of data. OLAP servers demand that decision support queries be acknowledged in the order of seconds. Thus, it is essential for data warehouse systems to provide highly effective cube computation techniques, access techniques, and query processing techniques.Efficient Computation of Data CubesAt the core of multidimensional data analysis is the efficient computation of aggregations across many sets of dimensions. In SQL terms, these aggregations are referred to as group-by’s. Each group-by can be represented by a cuboid, where the set of group-by’s forms a lattice of cuboids defining a data cube.There are three choices for data ... Read More

OLAP stands for On-Line Analytical Processing. OLAP is a categorization of software technology that authorizes analysts, managers, and executives to profit insight into information through quick, consistent, interactive access in a broad variety of possible views of information that has been transformed from raw data to reflect the real dimensionality of the enterprise as learned by the users.OLAP servers present business users with multidimensional data from data warehouses or data marts, without concerns regarding how or where the data are stored. The physical architecture and implementation of OLAP servers must consider data storage issues.There are three main types of OLAP ... Read More

Data Warehousing is a technique that is mainly used to collect and manage data from various sources to give the business a meaningful business insight. A data warehouse is specifically designed to support management decisions.In simple terms, a data warehouse refers to a database that is maintained separately from an organization’s operational databases. Data warehouse systems enables the integration of multiple application systems. They provide data processing by supporting a solid platform of consolidated, historical information for analysis.Data warehouses generalize and consolidate information in the multidimensional area. The construction of data warehouses includes data cleaning, data integration, and data transformation ... Read More

Data Warehouses usually have a three-level (tier) architecture that involves −The bottom tier is a warehouse database server that is relatively always a relational database system. Back-end tools and utilities are used to feed records into the bottom tier from operational databases or other external sources (including user profile data supported by external consultants).These tools and utilities implement data extraction, cleaning, and transformation (e.g., to merge the same data from multiple sources into a unified format), and load and refresh functions to update the data warehouse. The data are extracted using application program interfaces referred to as gateways.A gateway is ... Read More

A data warehouse can be built using three approaches −A top-down approachA bottom-up approachA combination of both approachesThe top-down approach starts with the complete design and planning. It is helpful in cases where the technology is sophisticated and familiar, and where the business issues that must be solved are clear and well-understood.The bottom-up approach starts with experiments and prototypes. This is beneficial in the beginning phase of business modeling and technology development. It enables an organisation to move forward at considerably less expense and to compute the advantage of the technology before creating significant commitments.In the combined approach, an organisation ... Read More