Integration Of Data Sources In Data Mining

After data cleaning steps in data mining. You need integration of data sources in data mining. It means combining disparate data sources into a single schematic structure. There are two major type of integration – schema integration and data integration. Schema integration forms an integrated schematic structure from the disparate data sources. The data integration … Read more

Transformation Algorithms

Once the dirty data is identified, we must use appropriate transformation rules on the data. Various transformation algorithms are help to solve different kind of problems with the data such as duplicate elimination, misspellings in the data. In this article, we will discuss some transformation algorithms. Hash-Merge for Duplicate Elimination Hash tuples based on given … Read more

Dirty Data And Data Cleaning

The first problem with data mining is that you need proper data. However, it is not possible if we talk about data from different sources. There is a couple of problem when data is from heterogeneous sources and it must be cleaned, transformed into a standard form to be mined. In this article, we will … Read more

Operational Database vs. Data Warehouse

In this article, we will evaluate operational database vs. data warehouse. Operational database is live database which uses normalization, concurrency control to manage transactions, and have a recovery mechanism. It is used by OLTP (Online Transaction Processing) applications. The data warehouse is kept separate from the OLTP databases. It is used by the OLAP( online … Read more

Data Warehouse Concepts

In this document, you will find all articles related to mining data and data warehouse. We will also briefly discuss about the OLTP and OLAP, data cleaning concepts. A data warehouse is “a copy of transaction data specifically structured for query and analysis“ Ralph Kimball Difference Between OLTP and OLAP Operational Database vs. Data Warehouse … Read more

Difference Between OLTP and OLAP

In the application world, there are two types of applications from the database perspective. Operational data and Historical data related to OLTP and OLAP applications respectively. In this article, we will you will learn the difference between OLTP and OLAP applications. Operations Data (OLTP applications) The operational data are those that “works”. It means these … Read more

Kind Of Patterns In Data Mining

Earlier we talked about mining patterns from data repositories. In this article, you will learn about kind of patterns in data mining. The pattern mining are tasks performed by the data mining engine. Later the patterns can be evaluated based on the interestingness measures. Mining Tasks The data mining tasks are classified into two categories … Read more

Kind of Data In Data Mining

Data mining uses a variety of techniques from multiple disciplines such as statistics, machine learning, high performance computing, pattern recognition, neural networks, data visualization, signal processing, and image processing. In addition to this, we must learn the kind of data in data mining. Data Sources Data mining is applied to all kinds of databases including … Read more

Data Mining Architecture And Its Components

We now discuss the data mining architecture and its components. We will learn about the functionality of each component and its role in the data mining system. These are the components that found in a typical data mining system. In some systems, the components are integrated into one, however, the functionality is different at different … Read more

What Are the Steps in Data Mining

In the previous article, you learned the purpose of data mining, which is to help various organizations, including businesses in extracting meaningful information. We are ready to discuss “What are the steps in data mining?” In the data mining process, each step does some tasks to make the mining process easier. We shall look into … Read more