converted into meaningful data (mostly Graphs and Images) •Intended to analyze complex data •Providing new answers to old questions •Developing new knowledge and understanding through discovery •Data from: Satellite Photos, Sonar Measurements, Surveys, or Computer Simulations
engineering can be referred as scientific data •In most of applications, hereby, we define scientific data as massive and digital data with a variety of data formats •Data can be floating-point data, integer data, image data, and clip data •Format are various. •Data dimensions (1-D, 2-D, 3-D or more)
find new, hidden, or unexpected patterns in data. •A data warehouse is main source where all data is stored. Example: databases •Research may be used for marketing or Customer Relationship Management.
an item belongs to a particular class of data • Two Sub-processes: • Building a Model • Predicting Classifications • Techniques that employ association search all details from operational systems for patterns with a high probability of repetition • Example: Market Basket Analysis Classification Association
on a series of preceding events • Through analysis, various hidden trends, often highly predictive of future events, can be discovered. • Example: Mail Industry • To create partitions so that all members of each set are similar according to some metric • Simply a set of objects grouped together by virtue of their similarity or proximity to each other • Example: Credit Card Transactions Sequence Cluster
Text Mining: Summarizes, navigates, and clusters documents contained in a database •Web Mining: Integrates data and text mining within a Web site; enhances the Web site with intelligent behavior, such as suggesting related links or recommending new products to the consumer
examines a long list of transactions in order to determine which items are most frequently purchased together. •It takes its name from the idea of a person in a supermarket throwing all of their items into a shopping cart (a "market basket").
data. •It is a specific area in visualization, although it utilizes the same or similar techniques as used in other visualization. •The data visualization deal with rare data, which is difficult to understand. •Closed with data analysis methods and techniques.