Data integration is the phase of combining data from several disparate sources. While implementing data integration, it should work on data redundancy, inconsistency, duplicity, etc. In data mining, data integration is a data pre-processing technique that contains merging data from numerous heterogeneous data sources into coherent data to retain and support a consolidated perspective of the information.It combines data from various sources into a coherent data store, including in data warehousing. These sources can involve multiple databases, data cubes, or flat files, etc. There are multiple issues to consider during data integration.Schema integration and object matching can be complex. For ... Read More

Data cleaning defines to clean the data by filling in the missing values, smoothing noisy data, analyzing and removing outliers, and removing inconsistencies in the data. Sometimes data at multiple levels of detail can be different from what is required, for example, it can need the age ranges of 20-30, 30-40, 40-50, and the imported data includes birth date. The data can be cleans by splitting the data into appropriate types.Types of data cleaningThere are various types of data cleaning which are as follows −Missing Values − Missing values are filled with appropriate values. There are the following approaches to ... Read More

Data mining is the procedure of finding useful new correlations, patterns, and trends by sharing 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.It is not limited ... Read More

The data mining system is integrated with a database or data warehouse system so that it can do its tasks in an effective presence. A data mining system operates in an environment that needed it to communicate with other data systems like a database system. There are the possible integration schemes that can integrate these systems which are as follows −No coupling − No coupling defines that a data mining system will not use any function of a database or data warehouse system. It can retrieve data from a specific source (including a file system), process data using some data ... Read More

Data mining functionalities are used to represent the type of patterns that have to be discovered in data mining tasks. In general, data mining tasks can be classified into two types including descriptive and predictive. Descriptive mining tasks define the common features of the data in the database and the predictive mining tasks act inference on the current information to develop predictions.There are various data mining functionalities which are as follows −Data characterization − It is a summarization of the general characteristics of an object class of data. The data corresponding to the user-specified class is generally collected by a ... Read More

Data mining defines extracting or mining knowledge from huge amounts of data. Data mining is generally used in places where a huge amount of data is saved and processed. For example, the banking system uses data mining to save huge amounts of data which is processed constantly.In Data mining, hidden patterns of data are considering according to the multiple categories into a piece of useful data. This data is assembled in an area including data warehouses for analyzing it, and data mining algorithms are performed. This data facilitates in creating effective decisions which cut value and increase revenue.There are various ... Read More

In telecommunication and electronics engineering, Bit Rate and Baud Rate are two commonly used terms in the context of data communication. Both these terms represent the speed of data transmission in the computer networks. The basic difference between Bit Rate and Baud Rate is that the Bit Rate is defined as the number of bits (binary 0s and 1s) transmitted over a network in unit time, whereas Baud Rate is defined as the number of signal units transmitted over a network in unit time. Thus, bit rate and baud rate both the related terms, and the relationship between these ... Read More

In parallel database system data processing performance is improved by using multiple resources in parallel. In this CPU, disks are used parallel to enhance the processing performance.Operations like data loading and query processing are performed parallel. Centralized and client server database systems are not powerful enough to handle applications that need fast processing.Parallel database systems have great advantages for online transaction processing and decision support applications. Parallel processing divides a large task into multiple tasks and each task is performed concurrently on several nodes. This gives a larger task to complete more quickly.Architectural ModelsThere are several architectural models for parallel ... Read More

In parallel database system data processing performance is improved by using multiple resources in parallel. In this CPU, disks are used parallel to enhance the processing performance. Operations like data loading and query processing are performed parallel. Centralized and client server database systems are not powerful enough to handle applications that need fast processing. Parallel database systems have great advantages for online transaction processing and decision support applications. Parallel processing divides a large task into multiple tasks and each task is performed concurrently on several nodes. This gives a larger task to complete more quickly. Architectural Models For Parallel Database ... Read More

In parallel database system data processing performance is improved by using multiple resources in parallel. In this CPU, disks are used parallel to enhance the processing performance. Operations like data loading and query processing are performed parallel. Centralized and client server database systems are not powerful enough to handle applications that need fast processing. Parallel database systems have great advantages for online transaction processing and decision support applications. Parallel processing divides a large task into multiple tasks and each task is performed concurrently on several nodes. This gives a larger task to complete more quickly. Architectural Models for Parallel DBMS ... Read More