0
A DBMS (Database Management System) is a complete system used for managing digital databases that allows storage of database content, creation/maintenance of data, search and other functionalities. On the other hand, Data Mining is a field in computer science, which deals with the extraction of previously unknown and interesting information from raw data. Usually, the data used as the input for the Data mining process is stored in databases. Users who are inclined toward statistics use Data Mining. They utilize statistical models to look for hidden patterns in data. Data miners are interested in finding useful relationships between different data elements, which is ultimately profitable for businesses.
DBMS
DBMS, sometimes just called a database manager, is a collection of computer programs that is dedicated for the management (i.e. organization, storage and retrieval) of all databases that are installed in a system (i.e. 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 means of allocation of different levels of privileges for different users, making it possible for a DBMS to be controlled centrally by a single administrator or to 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. The modeling language defines the language of each database hosted in the DBMS. Currently several popular approaches like hierarchal, network, relational and object are in practice. Data structures help organize the data such as individual records, files, fields and their definitions and objects such as visual media. Data query language maintains the security of the database by monitoring login data, access rights to different users, and protocols to add data to the system. SQL is a popular query language that is used in Relational Database Management Systems. Finally, the mechanism that allows for transactions help concurrency and multiplicity. That mechanism will make sure that the same record will not be modified by multiple users at the same time, thus keeping the data integrity in tact. Additionally, DBMS provide backup and other facilities as well.
Data Mining
Data mining is also known as Knowledge Discovery in Data (KDD). As mentioned above, it is a felid of computer science, which deals with the extraction of previously unknown and interesting information from raw data. Due to the exponential growth of data, especially in areas such as business, data mining has become very important tool to convert this large wealth of data in to business intelligence, as manual extraction of patterns has become seemingly impossible in the past few decades. For example, it is currently been used for various applications such as social network analysis, fraud detection and marketing. Data mining usually deals with following four tasks: clustering, classification, regression, and association. Clustering is identifying similar groups from unstructured data. Classification is learning rules that can be applied to new data and will typically include following steps: preprocessing of data, designing modeling, learning/feature selection and Evaluation/validation. Regression is finding functions with minimal error to model data. And association is looking for relationships between variables. Data mining is usually used to answer questions like what are the main products that might help to obtain high profit next year in Wal-Mart?
What is the difference between DBMS and Data mining?
DBMS is a full-fledged system for housing and managing a set of digital databases. However Data Mining is a technique or a concept in computer science, which deals with extracting useful and previously unknown information from raw data. Most of the times, these raw data are stored in very large databases. Therefore Data miners use the existing functionalities of DBMS to handle, manage and even preprocess raw data before and during the Data mining process. However, a DBMS system alone cannot be used to analyze data. But, some DBMS at present have inbuilt data analyzing tools or capabilities.
Wiki User
∙ 11y ago
Add your answer:
Earn +20 pts
What is the difference between OLAP and data mining?
difference between Data Mining and OLAP
Difference between traditional and latest DBMS package?
Traditional FPS and DBMS both are different from each other. In DBMS there is security of data as well as integrated data while this is not in FPS.
What is the need of rdbms?
A DBMS stores data in a table where the entries are filed under a specific category and are properly indexed. This allowed programmers to have a lot more structure when saving or retrieving data. A relational database contains data in more than one table. Each table contains a database that is then linked to other tables with respect to their relationships. Read more: Difference Between DBMS and RDMS | Difference Between | DBMS vs RDMS http://www.differencebetween.net/technology/difference-between-dbms-and-rdms/#ixzz1eJUZkRgz
Distinguish between Data mining and text mining?
mining the data is called data mining. Mining the text is called text mining
What is the difference between flat file and DBMS?
A flat file is a simple file containing data without any structured format, while a Database Management System (DBMS) is a software system that manages databases by organizing, storing, and retrieving data. A DBMS allows for more organized and efficient data management, supports relationships between data, and provides features like security and data integrity that are not available with flat files.
Major difference between dbms vs rdbms?
A DBMS (Database Management System) is a software that manages databases and provides functionalities to store, retrieve, and update data. An RDBMS (Relational Database Management System) is a type of DBMS that stores data in a structured way using tables with relationships between them. RDBMS enforces the relational model, which allows for data integrity through constraints and supports SQL for querying data.
What is difference between Schema and Subschema?
SCHEMA is the physical arrangement of the data as it appears in the DBMS. SUB-SCHEMA is the logical view of the data as it appears to the application program.
What are the difference between database systems and data information retrieval systems?
A database management system (DBMS or simply database) forms the back-end of a data information retrieval system. Data retrieval is just one component of a DBMS; data input, storage and maintenance being the other major components.
What are the key relationships between data warehouse and data mining?
Data warehouse is the database on which we apply data mining.
What is schema and sub-schema?
The schema is the physical arrangement of the data as it appears in the DBMS. The subschema is the logical view of the data as it appears to the application program.
Difference between discrimination and classification in datamining?
There is only a slight difference between discrimination and classification in data mining. Discrimination can be negative and classification is generally just factual.
What is the difference between OODBMS and DBMS?
Object-Oriented Database Management System (OODBMS) stores data in the form of objects with attributes and methods, allowing for complex data structures and relationships. Traditional Database Management System (DBMS) stores data in structured tables with rows and columns, focusing on relational data models. OODBMS is better suited for applications with complex data structures and relationships, while DBMS is more widely used for simpler data storage and retrieval needs.
