Data Analysis and Data Mining Can Innovate Your Enterprise

Data Analysis and Data Mining

Data is increasing exponentially as we speak. Computers across the globe gather an untold number of bits of information at any given time, and this can be overwhelming. Along with critical and useful information, there is so much data collected that may have no practical application in its raw form. Data warehouses, which are repositories where data is stored, may include a myriad of databases, metadata, or other electronic information in a variety of formats.

What Can Be Done To Make Sense Of This Huge Store Of Data?

Data analysis and data mining are part of business intelligence that can crunch information and produce useful results. Analysis includes querying and reporting, statistical analysis, and even more sophisticated multidimensional treatment of data. Data mining is an interdisciplinary sub-field of computing that involves knowledge discovery in databases.

While data mining has become a catch phrase for a wide variety of information processing, the proper use of the term involves discovering something new from the data. There are both automatic and semi-automatic methods of data mining. The term "data mining" appeared around 1990, and as a practice it continues to mature and become more necessary with the rapid growth of the digital universe. The process of data mining may involve cluster analysis, anomaly detection, or an analysis of data dependencies. Relationships investigated in data mining include classes, clusters, associations, and sequential patterns. Levels of analysis may involve decision trees, complex algorithms, rule induction, and data visualization.

Business analytics have become more sophisticated in recent years. Organizations who use the best data analysis and data mining tools may gain a competitive edge over others who are less data savvy. In fact, those who lag behind in this practice may find their information and business control efforts to be wasteful and inefficient. Innovation and efficiency are the keys to success for tech enterprises, and data analysis and data mining are becoming increasingly vital to that success.

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