DBMS vs. Data Mining

Difference Between DBMS and Data Mining

A DBMS (Database System Management) is a complete system used for direct digital databases that allows the storage of content database creation / maintenance of data, search and other functionalities. However, Data Mining is a field in computer science, which deals with the extraction of information previously unknown and interesting from raw data. Usually, the data used as input for the process of Data Mining are stored in databases. Users who are inclined to use statistics use data mining. They use statistical models to search for patters that are hidden in the data. Data miners find useful relations between data elements, which is good for business.

DBMS

DBMS, sometimes just called a database manager, is a collection of computer programs that is dedicated to the management (that is to say the organization, storage and recovery) of all databases that are installed in a system (that is to say the hard drive or network). There are different types of database management systems existing in the world and some of them are designed for the proper management of databases configured for specific purposes. Most popular commercial Database Management Systems are Oracle, DB2 and Microsoft Access. All these products provide a means for allocating different levels of privileges for different users, making it possible for a DBMS to be controlled by a central administrator or simply be allocated to several different people. There are four important elements in any database management system. They are the modeling language, data structures, query language and mechanism for transactions. Modeling language defines the language of each database hosted in the DBMS. Currently several popular approaches as hierarchal, network, relational and object are in practice. The assistance data structures organize the data as individual files, folders, fields and their definitions and objects such as visual mass media. Data Query Language maintains database security by checking login data and accessing different rights and protocols to different users. SQL is a query language that is used in delivery systems of relational database. Finally, the mechanism that takes into account transactions with the agreement and multiplicity will ensure that the same record will not be changed by multiple users at the same time maintaining the integrity of data in tact. Additionally, DBMS provide backup and other advantages as well too.

Data Mining

Data mining is also called Knowledge Discovery in Data (KDD). As stated above, it is a field of computer science, which handles the extraction of information that was previously unknown and interesting from raw data. Because of the exponential growth of data, especially in areas such as business, data mining has become very important instrument to convert this wealth of data to business intelligence, such as manual extraction of patterns that used to be seemingly impossible in a few decades ago. For example, it is used for different applications such as fraud detection, social network analysis and marketing. Data mining usually takes care of: classification, regression, clustering and the association. Clustering identifies similar groups of unstructured data. Classification learns the rules that can be applied to new data and include a characteristic way of following steps: preprocessing of data, designing the act of modeling, feature selection/learning and validation/evaluation. With the help of regression functions with minimum error to model data is detected. The association looks out for relations among variables. Data mining answers questions like which main products can help achieve high profit next year in Wal-mart?

What is the difference between DBMS and Data Mining?

DBMS is a system for housing and managing a set of digital databases. On the other hand data mining is a technique or concept in computing, which deals with the fact to extract useful and previously unknown information raw data. Most of the times, these raw data are kept in very large databases.  So the data miners use existing DBMS functionalities for handling, directing and even pre-process the raw data before and during the Data Mining process. Yet, a DBMS alone can not be used to analyze data. But a few DBMS data now have inbuilt tools or capabilities that can analyze data.

 

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