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 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

Data mart is a storage component and only cares about some specific functional area of an organisation which are then taken care by a single department like marketing, sales, finance etc. Data Mart and Data Warehouse are both storage components of HDFS. Data Mart contains a subset of the data stored in the data warehouse. Frequently requested data can easily be accessed through data mart. Simple to Implement and cost is lower as compared to data warehouse. It is more open to change and its smaller size makes it quicker to build if any change in model occurs. ... Read More

Data architecture design consists of standards which have certain rules, policies, data types to be collected, from where the data is collected, storage of data, arrangement of data, and then using that data for further analysis. Data plays a vital role in successful execution of business strategy. Data architecture design It helps us to show how users view the data in the database. It describes the type of data structures used to manage data and make the processing easy. the concept of dbms depends on its architecture. It is divided into three models i.e. conceptual model, logical model ... Read More

Anomalies means problems or inconsistency which happened during the operations performed on the table. There can be many reasons that anomaly occur for example, It occurs when data is stored multiple times unnecessarily in the database i.e. redundant data is present or it occur when all the data is stored in a single table. normalization is used to overcome the anomalies. the different type of anomalies are insertion, deletion and updation anomaly. Input The same input is used for all three anomalies. Student ID Name Age Branch Branch_Code Hod_name 1 A 17 Civil 101 Aman ... Read More

It is used to return the name of the current user in sql database server. it does not accept any parameter. Syntax CURRENT_USER Current_user is the function used to get the name of current user Example 1 In this example, we are going to use the current_user function to get the current user name. Input Employee Emp_id Name Dept_name Salary 1 Monu IT 50000 2 Sonu HR 60000 3 Golu Security 70000 This database is currently used by amrendra. Code SELECT CURRENT_USER;#selected current user name Output Amrendra ... Read More

A materialised is defined as a database object that contains the results of a particular query. It could be called as a subset of a table. Any changes in the base table would be reflected in the materialised view. Syntax CREATE MATERIALISED VIEW view_name AS SELECT * FROM table_name WHERE column_name IS NOT NULL PRIMARY KEY (provide_primary_key) Here, view_name is the name of the materialised view, table_name is the base table, column_name are the columns provide_primary_key are the primary keys for the base table. Example 1 In this example, we are gonna have a ... Read More