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A data warehouse can be built using three approaches −A top-down approachA bottom-up approachA combination of both approachesThe top-down approach starts with the complete design and planning. It is helpful in cases where the technology is sophisticated and familiar, and where the business issues that must be solved are clear and well-understood.The bottom-up approach starts with experiments and prototypes. This is beneficial in the beginning phase of business modeling and technology development. It enables an organisation to move forward at considerably less expense and to compute the advantage of the technology before creating significant commitments.In the combined approach, an organisation ... Read More
Data Warehousing is a technique that is mainly used to collect and manage data from various sources to give the business a meaningful business insight. A data warehouse is specifically designed to support management decisions.In simple terms, a data warehouse defines a database that is maintained independently from an organization’s operational databases. Data warehouse systems enable the integration of several application systems. They provide data processing by supporting a solid platform of consolidated, historical information for analysis.The technology of the Data warehouse includes data cleaning, data integration, and online analytical processing (OLAP), that is, analysis techniques with functionalities such as ... Read More
The major components of a data warehouse are as follows −Data Sources − Data sources define an electronic repository of records that includes data of interest for administration use or analytics. The mainframe of databases (e.g. IBM DB2, ISAM, Adabas, Teradata, etc.), client-server databases (e.g. Teradata, IBM DB2, Oracle database, Informix, Microsoft SQL Server, etc.), PC databases (e.g. Microsoft Access, Alpha Five), spreadsheets (e.g. Microsoft Excel) and any other electronic storage of data.Data Warehouse − The data warehouse is normally a relational database. It should be organized to hold data in a structure that best supports not only query and ... Read More
Data Warehousing is a technique that is mainly used to collect and manage data from various sources to give the business a meaningful business insight. A data warehouse is specifically designed to support management decisions.In simple terms, a data warehouse refers to a database that is maintained separately from an organization’s operational databases. Data warehouse systems enable for integration of several application systems. They provide data processing by supporting a solid platform of consolidated, historical information for analysis.Data Warehouse queries are complicated because they contain the computation of huge groups of information at summarized levels. It can require the use ... Read More
If we have a data set that contains missing values at alternate places for each column then we might want to combine the columns by excluding those missing values, this will reduce the data set and the analysis is likely to become easier.For this purpose, we can use na.exclude function along with apply function as shown in the below given examples.Example 1Following snippet creates a sample data frame −x1
Data Warehousing is a technique that is mainly used to collect and manage data from various sources to give the business a meaningful business insight. A data warehouse is specifically designed to support management decisions.In simple terms, a data warehouse defines a database that is maintained independently from an organization’s operational databases. Data warehouse systems enable the integration of multiple application systems. They provide data processing by offering a solid platform of consolidated, historical information for analysis.Data warehouses generalize and centralize data in multidimensional space. The construction of data warehouses contains data cleaning, data integration, and data transformation and can ... Read More
To create a colored box for base R plot, we can use box function with col argument where we can pass the color other than black because black is the default color.We first need to create the plot using plot function and then box function will be used as shown in the below given example.ExampleTo create a colored box for base R plot, use the following code −plot(1:5) box(lwd=5, col="blue")OutputIf you execute the above given code, it generates the following output −To create a colored box for base R plot, use the following code −plot(1:5) box(lwd=10, col="red")OutputIf you execute the ... Read More
Data integration is the procedure of merging data from several disparate sources. While performing data integration, it must work on data redundancy, inconsistency, duplicity, etc. In data mining, data integration is a record preprocessing method that includes merging data from a couple of the heterogeneous data sources into coherent data to retain and provide a unified perspective of the data.Data integration is especially important in the healthcare industry. Integrated data from several patient records and clinics assist clinicians in identifying medical disorders and diseases by integrating information from several systems into a single perspective of beneficial information from which useful ... Read More
If we know the total number of rows we want in our matrix and the number of columns then we can use matrix function to create a matrix by filling the data with predefined values. These values must be equal to the multiplication of number of rows and columns.Check out the below given examples to understand how it works.Example 1Following snippet creates a matrix in R by filling the data with predefined values in loop −n=20 k=2 data=rpois(n*k, 5) M1=matrix(data, nrow=n, ncol=k) M1If you execute the above given snippet, it generates the following output − [, 1] [, 2] ... Read More
The autocorrelation plot or ACF plot is a display of serial correlation in data that changes over time. The ACF plot can be easily created by using acf function.For example, if we have a vector called V then we can create its autocorrelation plot by using the command given below −acf(V)Check out the below examples to understand how it can be done.Example 1To create ACF plot in R, use the code given below −x