Article Categories
- All Categories
-
Data Structure
-
Networking
-
RDBMS
-
Operating System
-
Java
-
MS Excel
-
iOS
-
HTML
-
CSS
-
Android
-
Python
-
C Programming
-
C++
-
C#
-
MongoDB
-
MySQL
-
Javascript
-
PHP
-
Economics & Finance
Articles on Trending Technologies
Technical articles with clear explanations and examples
What are the tools and utilities of a data warehouse?
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 enables the integration of multiple application systems. They provide data processing by supporting a solid platform of consolidated, historical information for analysis.Data warehouses generalize and consolidate information in the multidimensional area. The construction of data warehouses includes data cleaning, data integration, and data transformation ...
Read MoreHow to create a scatterplot with white background and no gridlines using ggplot2 in R?
Practically, the scatterplots are well visualized on white background just like on white paper. If we want to create a scatterplot with white background and without gridlines using ggplot2 then we can apply classic theme to the plot.Check out the below given example to understand how it can be done.ExampleFollowing snippet creates a sample data frame −x
Read MoreWhat is a Three-tier Data Warehouse Architecture?
Data Warehouses usually have a three-level (tier) architecture that involves −The bottom tier is a warehouse database server that is relatively always a relational database system. Back-end tools and utilities are used to feed records into the bottom tier from operational databases or other external sources (including user profile data supported by external consultants).These tools and utilities implement data extraction, cleaning, and transformation (e.g., to merge the same data from multiple sources into a unified format), and load and refresh functions to update the data warehouse. The data are extracted using application program interfaces referred to as gateways.A gateway is ...
Read MoreHow to find the number of unique values in comma separated strings stored in an R data frame column?
If we have comma separated values that contains duplicate and unique values then we might want to find the number of unique values within each comma separated value. To find the unique values in comma separated strings stored in an R data frame column, we can use stri_extract_all_regex function of stringi package along with sapply function.Check out the below examples to understand how it can be done.Example 1Following snippet creates a sample data frame −x
Read MoreWhat is the process of data warehouse design?
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 MoreWhy do Business Analysts need Data Warehouse?
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 MoreWhat are the components of a data warehouse?
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 MoreWhy do we need a separate Data Warehouse?
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 MoreHow to combine columns by excluding missing values in R?
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
Read MoreWhat is Data Cube Aggregations?
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