Data cleaning problems and current approaches ppt

While many data mining tasks follow a traditional, hypothesis-driven data analysis approach, it is commonplace to employ an opportunistic, data driven approach that encourages the pattern detection algorithms to find useful trends, patterns, and relationships. Essentially, the two types of data mining approaches differ in whether they seek to build

Data Quality Issues and Current Approaches to Data Cleaning Process in Data Warehousing Jaya Bajpai Pravin S. Metkewar MBA-IT Student Associate Professor SICSR, affiliated to Symbiosis International University (SIU), Pune, and Maharashtra, India SICSR, affiliated to Symbiosis International University (SIU), Pune, and Maharashtra, India Abstract

Data Mining - Issues - Data mining is not an easy task, as the algorithms used can get very complex and data is not always available at one place. It needs to be integrated from vario online, directly into a database, or first on a paper form and then typed or even scanned into a computer data - base. Whatever data entry method is used, the data must be checked carefully for errors—a process called data cleaning. Most survey research organizations now use a database management program to monitor data

A clear reply is that database is cleaned up through the use of cleaning software. This software is specifically programmed to manage irrelevant, contemporary, damage.. Importance of Data Cleansing Techniques |authorSTREAM