DATA MINING

Cluster analysis or simply clustering is the process of partitioning a set of abstract data objects (or observations) into subsets. Each subset is a cluster, such that objects in a cluster are similar to one another, yet dissimilar to objects in other clusters. Overview Of Basic Clustering Methods:Partitioning methods:Hierarchical methods: Agglomerative versus Divisive Hierarchical Clustering:Density-based methods:DBSCAN algorithm requires two parameters: The set of clusters resulting from a cluster analysis can be referred to as a…

Grid-based methods quantize the object space into a finite number of cells that form a grid structure. All the K-Means clustering operations are performed on the grid structure (i.e., on the quantized space). New Trick Data Mining In Grid-Based and K-Means Methods  K-Means: A Centroid based technique: Data Mining Applications:Data Mining for Financial Data Analysis - Design and construction of data warehouses for multidimensional data analysis and Data mining:Classification and clustering of customers for targeted marketing:Detection…

Data cleaning is one of the important parts of machine learning. It plays a significant part in building a model. Data Cleaning is one of those things that everyone does but no one really talks about. It surely isn't the fanciest part of machine learning and at the same time, there aren't any hidden tricks or secrets to uncover. However, proper data cleaning can make or break your project. Professional data scientists usually spend…

In the Information Industry, a vast amount of data is available but is not useful until it undergoes data processing to extract valuable information. Data processing involves various essential steps such as Data Cleaning, Data Integration, Data Transformation, Data Mining, Pattern Evaluation, and Data Presentation. Once these processes are completed, the information can be utilized in applications like Fraud Detection, Market Analysis, Production Control, and Science Exploration. There is a huge amount of data…

A business Analysis Framework for Data Warehouse Design . The business analyst get the information from the data warehouses to measure win performance and make critical adjustments in order to win over other business holders in the market. Data warehouse offers the following advantages: it can enhance business productivity as gathering information quickly and efficiently it helps us manage customer relationship by a consistent view of customers and items it helps in bringing down…

Data Cube is a structure that enables OLAP to achieve multidimensional functionality. It is used to represent data with some measure. It is an easy way to look at the complex data into a simple format. It allows data to modeled and viewed in multiple dimensions. Cube is defined by facts and dimensions. It can be 2-dimensional, 3-dimensional or higher-dimensional. It ensures report optimization through efficient data retrieval. In data warehouse architecture, a data…

A Data Warehousing (DW) is the process for collecting and managing data from varied sources to provide meaningful business insights. It is typically used to connect and analyze business data from heterogeneous sources. It the core of the BI System which is built for data analysis and reporting. It is an Electronic storage of a large amount of information by a business which is designed for query and analysis instead of transaction processing. It…

Data mining and Data Warehouse algorithms embody techniques that have sometimes existed for many years, but have only lately been applied as reliable and scalable tools that time and again outperform older classical statistical methods. While data mining is still in its infancy, it is becoming a trend and ubiquitous. Before data mining develops into a conventional, mature and trusted discipline, many still pending issues have to be addressed. Some of these issues are…

Data mining is primarily used by industries that cater to the consumer, like retail, financial and marketing companies. If you've ever shopped at a retail store and received customized coupons, that's a result of mining. Your individual purchase history was analyzed to find out what products you've been buying and what promotions you're likely to be interested in. Netflix uses data mining to recommend movies to its customers ,Google uses mining to tailor advertisements…