What is Data preprocessing? Data preprocessing is a data mining technique that involves transforming incomplete, inconsistent, and/or noisy data which increase chances of error and misinterpretation, into an understandable format. Incomplete: Lacking attribute values, lacking certain attributes of interest, or containing only aggregate data. E.g., occupation = “” Noisy: NoisyRead More →

In several sectors, data mining and knowledge discovery is becoming a critical technology for businesses and researchers. While data mining is becoming a well-established and reputable subject, there are still numerous difficulties to overcome. Some of the challenges are: Mining methodology and user interaction issues  It refers to the followingRead More →

Data sets are made up of data objects.  A data object represents an entity.  Examples: – sales database: customers, store items, sales – medical database: patients, treatments – university database: students, professors, courses . Also called samples , examples, instances, data points, objects, tuples.   Data objects are described by attributes. Read More →

Knowledge Discovery in Databases (KDD) Knowledge Discovery in a database is the process of discovering useful knowledge from a collection of data .This widely used data mining technique is a process that includes data preparation and selection, data cleansing incorporating prior knowledge on data sets and interpreting accurate solutions fromRead More →

Data mining functions are used to define the kind of patterns that will be discovered during data mining jobs. Some of the major data mining functionalities are as follows:  Class/ concept descriptions: Characterization and Discrimination Class/concept descriptions are the definitions of a class or idea. Data features should be generalised,Read More →

Motivation for Data Mining Over the last three decades, the steady and remarkable advancement of computer hardware technology has resulted in a large supply of powerful and affordable computers, data collection equipment, and storage media. This technology provides a significant boost to the database and information industries, allowing for theRead More →

Components of Data Warehouse A typical data warehouse consists of four major components: a central database, ETL (extract, transform, and load) tools, metadata, and access tools. All of these components are designed to work rapidly, allowing you to acquire findings and analyze data on the fly. The following are theRead More →

The conceptual data model is a structured business view of data required to support business, processes,record business events and track related performance measures. This model focuses on identifying data  used in business but not its processing flow or physical characteristics. It is a concise description of the user’s data requirementsRead More →