Found 428 Articles for DBMS

Data Definition Language(DDL) is used for describing data and its relationship in a database. It is also used to define the database schema. The commands only affect the database structure and not the data. The main DDL commands are create, alter, drop and truncate. Create Statement It is used to create a database or table. While creating the table, we specify table_name, column_name followed by data_types(int, float, varchar, etc) and constraints(primary key, not null, etc) Syntax CREATE TABLE table_name ( column1 datatype, column2 datatype, ..... ) Example In this ... Read More

DCL(Data Control Language) work is to deal with sql commands that are used to permit a user to access, modify and work on a database. it is used to access stored data. It gives access, revoke access and change the permission to the owner of the database as per the requirement. It helps in how sql can use a user authority to modify or retrieve data and protect against unauthorised access. It complements data manipulation language(DML) and data definition language(DDL). It is the simplest among the three command It is basically used for enforcing data security. DCL Commands ... Read More

Data replication means copying the data at multiple locations to improve the availability of data. It is used to remove the inconsistency between the same data which results in a distributed database so that users can do their own task without interrupting the work of other users. There are various types of Data Replication in DBMS as follow − Types of Data Replication Transactional Replication It makes a full copy of the database along with the changed data. Transactional consistency is guaranteed because the order of data is the same when copied from publisher to subscriber database. It is ... Read More

Data preprocessing is an important process of data mining. In this process, raw data is converted into an understandable format and made ready for further analysis. The motive is to improve data quality and make it up to mark for specific tasks. Tasks in Data Preprocessing Data cleaning Data cleaning help us remove inaccurate, incomplete and incorrect data from the dataset. Some techniques used in data cleaning are − Handling missing values This type of scenario occurs when some data is missing. Standard values can be used to fill up the missing values in a manual way but ... Read More

Data Objects Data objects refers to a collection of various attributes which are combined to make it understandable. Data object values have their own unique id, attribute and data types. The most common type is the data table. Data objects are mostly represented in data models, which resolve with the relationship among the data objects. Types of Data Objects Array is a one-dimension data object. i.e, can be a single column in a table. Example Student Name Aman Naman Monu Records Records refers to a single row for every ... Read More

Data Models Data models refers to how the logical structure of a database is made. Data model acts as a conceptual tool that describes the data relationship, data semantics and data constraints. Database uses three tier architecture so we need to design the database at physical, logical and view level. Categories of data model are − Relational Data Model In this model, the data is designed in form of rows and column within a table. The tables are then going to establish the relationship among the data. Tables are referred as relations because the relationship among the table or data ... Read More

Data modeling refers to the process of handling and designing the data model within a data warehouse platform. It consists of making an appropriate database schema so as to transfer the data that can be stored and of useful to user. Data warehouse modeling is used for two reasons, first is that relationship within the warehouse data can be visualised through the schema and second is that the cost is reduced and efficiency is increased with the help of well-designed schema which allow effective data warehouse structure to occur. Data modeling is different in data warehouse than in operational database ... Read More

Data Mining The process of extracting the data from a huge dataset that can be used for analysis and benefit of the organisation. This process helps in identifying patterns and managing relationship among the data to predict business problems. Data attributes An attribute can be defined as characteristics or property of an object. Object is described by attributes set and is referred to as a record of entity. Entity is described by a fraction of data i.e. attributes. For Example:In a Student database. (Name, id, Roll_no, Marks) are the attributes in provided database. Types of Attributes Nominal Attribute It only ... Read More

The process of extracting the data from a huge dataset that can be used for analysis and benefit of the organization. Data mining process generally involves the following steps − Business understanding Business understanding and client objective is necessary. Clients needs are to be defined and then using the scenario, data mining goals are defined. Data understanding Data is collected from different sources and explored to understand the properties and characteristics of data. Data preparation The data that is being collected are now selected, cleaned, transformed, preprocessed and constructed so as to make it ready for analysis. This process takes ... Read More

Association rule mining helps us to find relationships among large dataset. In Multidimensional association, Multidimensional association rule comprises of more than one aspect Numeric attributes should be discretized. Attributes can be unmitigated or quantitative. Quantitative characteristics are numeric and consolidate pecking order. Three approaches in mining multidimensional association rules are − Using static discretization of quantitative attributes Discretization happens earlier to mining and is static. Discretized attributes are treated as absolute and use an algorithm called apriori algorithm to search for all k-frequent predicate sets(k or k+1 table scans are required). Each subset of a frequent predicate set ... Read More