In the current era, we are flooded with data but Data is basically a dead item unless it is processed to get output in the form of information. Perfect information is a myth, and derived information is person dependent. Solution to the data explosion problem is Data Warehousing & Data Mining. It could be used for extracting interesting information in the form of rules, regularities, trends, patterns & constraints from the data stored in large warehouses.
Knowledge is more proactive in nature, and conveys understanding or learning from a problem or activity. it generally helps in discovering trend, pattern, sequence, association, anomaly, deviation, outliers, clustering, prediction, regression, time series and forecasting. Data Mining is nothing but knowledge discovery of interesting, useful, actionable, valid information or patterns from data warehouses. The discovery could be non-trivial, previously unknown, potentially useful or implicit. Data Mining is alternatively known as Knowledge discovery in databases, business intelligence, data analysis, information harvesting or data archaeology.
Data Mining is convergence of multiple disciplines comprising Machine learning, statistics, database systems, algorithms and depictions. Data Mining could be categorized into Discovering information, Predictive analysis and Investigative analysis, leading to Inference, Association, outcome prediction, forecasting, link establishment and deviation. Multiple data bases lead to data integration that is then cleansed for warehousing. Basis objective the selection and reduction of data provides you task-oriented data for performing data mining, resulting in pattern evaluation that translates to Knowledge.
Please keep watching this space for more learning on Information Management topic!
Comments