Computer network security has never been as critical as it is today. The news is littered with the widespread incidents of hacking and cyber theft in the financial, entertainment, and retail industries, and more recently in our military. A recent survey, conducted by Kaspersky Lab, a leader in endpoint protection solutions, found that 94% of all companies surveyed experienced a cyber security issue (Kaspersky Lab, 2014). Furthermore, a recent study has found that the average cost of a data breach to a company was $3.5 million, a 15% increase from the previous year (Ponemon Institute, 2014). In this day and age, the cost of a data breach, not only to a company’s bottom line, but to their reputation, would be extensive.
Data mining is a combination of database and artificial intelligence technologies. Although the AI field has taken a major dive in the last decade; this new emerging field has shown that AI can add major contributions to existing fields in computer science. In fact, many experts believe that data mining is the third hottest field in the industry behind the Internet, and data warehousing.
The data mining tasks are the kinds of patterns that can be mined. There are many tasks in data mining, the most common ones are: Association, classification, clustering and outlier detections. In the following sections describes the results of applying data mining techniques to the data of our case study for each of the four tasks.
Data mining is finding the routines and examples in large databases to guide choices about future exercises. It is normal that data mining tools to get the model with negligible information from the client to identify. Data mining is the utilization of automated data analysis techniques to discover already undetected connections among data things. It regularly determines the
With rapid advancements in the technology, new concepts are hitting the industry and it is redefining itself over a course of time. The data mining is one of its kind to improvise the lives of people. Data mining uses techniques which are helpful in finding out the different forms of data. The data mining is closely related to the database technology. Almost every industry takes the help of the datamining to grow in their respective fields. For instance, stock management, quality control, risk management, fraud detection, marketing and analysis of investments. It has its applications ranging from finding the molecule structure of the gene to identifying a robbery at an international level.
To begin with, Dell software an information technology enterprises describes Data Mining as “an analytic process designed to explore data in search of consistent patterns and/or systematic relationships between variables, and then to validate the findings by applying the
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 gain competitive advantage, improve processes, gain efficiency, save costs, utilizing and allocating resources optimally.
Data mining is not another hype. Instead, the need for data mining has arisen due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge. Thus, data mining can be viewed as the result of the natural evolution of information technology.
Data Mining. It is the process of discovering interesting knowledge that are gathered and significant structures from large amounts of data stored in data warehouse or other information storage.
Today with the ever growing use of computers in the world, information is constantly moving from one place to another. What is this information, who is it about, and who is using it will be discussed in the following paper. The collecting, interpreting, and determination of use of this information has come to be known as data mining. This term known as data mining has been around only for a short time but the actual collection of data has been happening for centuries. The following paragraph will give a brief description of this history of data collection.
Data Mining is an analytical process that primarily involves searching through vast amounts of data to spot useful, but initially undiscovered, patterns. The data mining process typically involves three major stepsexploration, model building and validation and finally, deployment.
Data mining uses computer-based technology to evaluate data in a database and identify different trends. Effective data mining helps researchers predict economic trends and pinpoint sales prospects. Data mining is stored in data warehouses, which are sophisticated customer databases that allow managers to combine data from several different organization functions.
Data Mining, a sub-branch of computer science, involving statistics, methods and calculations to find patterns in large amount of data sets, and database systems. Generally, data mining is the process to examine data from different aspects and summarizing it into meaningful information. Data mining techniques depict actions and future trends, allowing any individual to make better and knowledge-driven decisions.[1][2]
As coined in an article in the St. Louis Post-Dispatch by Aisha Sultan, “Data is the new world currency.” Data mining is the process of analyzing data from different perspectives and then summarizing it into useful information. In essence is it applying all different types of what if scenarios on large swaths of data to get possible results to aid in better decision making. This sort of decision making isn’t something new, it’s the technology aiding the decision making that is new. This has reduced the amount of time it takes in the decision making process and given the
Safety of information is the most valuable asset in any organization particular those who provide financial service to others. Threats can come from a variety of sources such as human threats, natural disasters and technical threats. By identifying the potential threats to the network, security measure can be taken to combat these threats, eliminate them or reduce the likelihood and impact if they should occur.