The objective of any data analysis is to obtain actionable information related to business. For managers working on the data domain, to support business decisions and actions, understanding of the theories and techniques in the data analysis fields such as statistics, data mining, and predictive analytics is very important.
Data visualization is the effort to help people understand the significant information in the data by showing it in a visual context. The data visualization is one of the most important analysis techniques today when the world is full of data. It is especially useful when we seek to understand insights from a large volume of data quickly. The computer graphics and animation are the most popular forms of this technique.
Data mining, sometimes called data or knowledge discovery, is a process of data analysis designed to work with large volumes of data to detect patterns, relationships or relevant information that can improve the performance. For example, a retailer uses data mining to analyze local buying patterns, or a credit card companies suggest products to their cardholders based on the analysis of their monthly expenditures.
The Neural Networks technique can be used to extract patterns and detect trends that are too complex to be identified by either humans or other computer techniques. The trained neural network can be thought of an expert who is able to provide projections with the given situations and answer the “what if” questions.
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