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Database Articles
Page 176 of 547
What is KDD?
KDD represents Knowledge Discovery in Databases. It defines the broad process of discovering knowledge in data and emphasizes the high-level applications of definite data mining techniques. It is an area of interest to researchers in several fields, such as artificial intelligence, machine learning, pattern recognition, databases, statistics, knowledge acquisition for professional systems, and data visualization.The main objective of the KDD process is to extract data from information in the context of huge databases. It does this by utilizing Data Mining algorithms to recognize what is considered knowledge. The Knowledge Discovery in Databases is treated as a programmed, exploratory analysis and ...
Read MoreWhat is the History of Data Mining?
Data mining is the process of finding useful new correlations, patterns, and trends by transferring through a high amount of data saved in repositories, using pattern recognition technologies including statistical and mathematical techniques. It is the analysis of factual datasets to discover unsuspected relationships and to summarize the records in novel methods that are both logical and helpful 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 is similar ...
Read MoreWhy do we need KDD?
The traditional techniques of turning data into knowledge depend on manual analysis and interpretation. For instance, in the healthcare industry, it is familiar for specialists to systematically analyze current trends and changes in healthcare data, every quarter.The specialists support a report detailing the analysis to the sponsoring healthcare organization; this report becomes the basis for future decision making and planning for healthcare management. There are several types of applications, including planetary geologists sifting through remotely sensed images of planets and asteroids, carefully situating and cataloging such geologic objects of interest as impact craters.This form of manual probing of a data ...
Read MoreWhat are Data Warehouse Users?
Data Warehousing is a technique that is generally used to collect and manage data from multiple sources to provide the business a meaningful business insight. A data warehouse is specifically created for the goals of 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 data for analysis.There are various types of data warehouse users which are as follows −Statisticians − There are generally only a handful of ...
Read MoreDifference between a data warehouse database and an OLTP database?
Data Warehouse DatabaseData Warehousing is a technique that is generally used to collect and manage data from multiple sources to provide the business a meaningful business insight. A data warehouse is specifically created for the goals of 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 data for analysis.A data warehouse provides an OLTP system by supporting a place for the OLTP database to offload data as ...
Read MoreWhat is the design of quality driven data warehouse?
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 support data processing by supporting a solid platform of consolidated, historical records for analysis.A data warehouse can be viewed as a set of materialized views represented over remote base relations. When a query is formal, it is computed locally, using the materialized views, without accessing the initial data sources.The data warehouse is an active entity that derives continuously over time. As time passes, new queries are required to be answered by them. Various queries ...
Read MoreWhat is Data Staging?
In the data warehousing process, the data staging area is collected of the data staging server software and the data store archive (repository) of the results of extraction, transformation, and loading activity.The data staging software server temporarily saves and changes data extracted from OLTP data sources and the archival repository stores cleaned, transformed data and attributes for loading into data marts and data warehouses.The data staging process imports information either as streams or files, change it, produces integrated, cleaned data, and stages it for loading into data warehouses, data marts, or Operational Data Stores.A data staging tool is accessible, and ...
Read MoreWhat is the structure of the data warehouse?
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 −Physical store − A Microsoft SQL Server database that it can query using SQL queries, and an OLAP database that it can need to run reports.Logical schema − A conceptual model that maps to the data in the physical store.Physical StoreThe physical store for the Data Warehouse contains one database ...
Read MoreWhat is Metadata Hub?
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 of Metadata among systems and products in a shared Meta data environment. The hub must have a record and open programmatic object interface (employing COM or CORBA, for example) that allows third-party tools to control the services of the hub. A file transfer structure supporting industry-identified file formats (comma delimited ...
Read MoreWhat are the types of data warehouse quality?
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 ...
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