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Data Structure Articles
Page 144 of 164
What are the types of OLAP Servers?
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 MoreWhat are the tools and utilities of a data warehouse?
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 MoreWhat is a Three-tier Data Warehouse Architecture?
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 MoreWhat is the process of data warehouse design?
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 MoreWhy do Business Analysts need Data Warehouse?
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 defines a database that is maintained independently from an organization’s operational databases. Data warehouse systems enable the integration of several application systems. They provide data processing by supporting a solid platform of consolidated, historical information for analysis.The technology of the Data warehouse includes data cleaning, data integration, and online analytical processing (OLAP), that is, analysis techniques with functionalities such as ...
Read MoreWhat are the components of a data warehouse?
The major components of a data warehouse are as follows −Data Sources − Data sources define an electronic repository of records that includes data of interest for administration use or analytics. The mainframe of databases (e.g. IBM DB2, ISAM, Adabas, Teradata, etc.), client-server databases (e.g. Teradata, IBM DB2, Oracle database, Informix, Microsoft SQL Server, etc.), PC databases (e.g. Microsoft Access, Alpha Five), spreadsheets (e.g. Microsoft Excel) and any other electronic storage of data.Data Warehouse − The data warehouse is normally a relational database. It should be organized to hold data in a structure that best supports not only query and ...
Read MoreWhy do we need a separate Data Warehouse?
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 enable for integration of several application systems. They provide data processing by supporting a solid platform of consolidated, historical information for analysis.Data Warehouse queries are complicated because they contain the computation of huge groups of information at summarized levels. It can require the use ...
Read MoreWhat is Data Cube Aggregations?
Data integration is the procedure of merging data from several disparate sources. While performing data integration, it must work on data redundancy, inconsistency, duplicity, etc. In data mining, data integration is a record preprocessing method that includes merging data from a couple of the heterogeneous data sources into coherent data to retain and provide a unified perspective of the data.Data integration is especially important in the healthcare industry. Integrated data from several patient records and clinics assist clinicians in identifying medical disorders and diseases by integrating information from several systems into a single perspective of beneficial information from which useful ...
Read MoreWhat are the techniques of Discretization and Concept Hierarchy Generation for Numerical Data?
It is complex and laborious to define concept hierarchies for numerical attributes because of the broad diversity of applicable data ranges and the frequent updates of data values. There are various methods of concept hierarchy generation for numeric data are as follows −Binning − Binning is a top-down splitting technique based on a defined number of bins. These methods are also used as discretization methods for numerosity reduction and concept hierarchy generation. These techniques can be used recursively to the resulting partitions to make concept hierarchies. Binning does not use class data and is, therefore, an unsupervised discretization technique. It ...
Read MoreWhat is Data Discretization?
The data discretization techniques can be used to reduce the number of values for a given continuous attribute by dividing the range of the attribute into intervals. Interval labels can be used to restore actual data values. It can be restoring multiple values of a continuous attribute with a small number of interval labels therefore decrease and simplifies the original information.This leads to a concise, easy-to-use, knowledge-level representation of mining results. Discretization techniques can be categorized depends on how the discretization is implemented, such as whether it uses class data or which direction it proceeds (i.e., top-down vs. bottom-up). If ...
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