DATA MINING, PROCESS & TECHNIQUES

     DATA MINING & ITS BENEFITS   

            Data mining, also known as wisdom find in data (KDD), encountered patterns and valuable data from large data clusters. Given the growth of data warehousing technology and the development of big data, the adoption of data mining methods has rapidly revved over the last duo of decades, aiding firms by recasting their raw data into useful knowledge. However, even though that technology constantly develops to manage data at a large scale, leaders still face challenges with scalability and mechanization.

            Data mining has enhanced executive decision-making via insightful data examinations. The data mining techniques that underpin these researches can be divided into two main purposes; they can either describe the target dataset or predict outcomes through apparatus learning algorithms. In addition, these methods are used to manage and filter data, surfacing the most interesting information, from fraud detection to user manners, back-ups, and even security breaches.

Data Mining Process :

1. Set the business objective
2. Data preparation
3. Model Building and Pattern mining
4. Evolution of results
5. Implementation of knowledge                         

Data Mining Techniques :

1. Association Rule   
2. Neural Networks
3. Decision Tree
4. K-Nearest Neighbour