Data Warehousing and Data

1171 Words5 Pages
Data mining can discover information hidden within valuable data assets. Knowledge discovery, using advanced information technologies, can uncover veins of surprising, golden insights in a mountain of factual data. Data mining consists of panoply of powerful tools, which are intuitive, easy to explain, understandable, and simple to use. These advanced information technologies include artificial intelligence methods, decision trees, rule induction methods, genetic algorithms and genetic programming, neural networks, and clustering techniques. The synergy created between data warehousing and data mining allows knowledge seekers to leverage their massive data assets, thus improving the quality and effectiveness of their decisions • Explain the benefits and current trends of data warehousing and data mining. Dramatic advances in data capture, processing power, data transmission, and storage capabilities are enabling organizations to integrate their various databases into data warehouses. Data warehousing is defined as a process of centralized data management and retrieval. Data warehousing, like data mining, is a relatively new term although the concept itself has been around for years. Data warehousing represents an ideal vision of maintaining a central repository of all organizational data. Centralization of data is needed to maximize user access and analysis. Dramatic technological advances are making this vision a reality for many companies. And, equally dramatic advances in data analysis software are allowing users to access this data freely. The data analysis software is what supports data mining. Generally, data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information – information that can be used to increase revenue, cuts costs, or both. Data
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