Data Mining vs Query Tools
Query Tools are tools that help analyze the data in a database. They provide query building, query editing, searching, finding, reporting and summarizing functionalities. On the other hand, Data mining is a field in computer science, which deals with the extraction of previously unknown and interesting information from raw data. Data used as the input for the Data mining process usually is stored in databases. Users who are inclined toward statistics use Data Mining. They utilize statistical models to look for hidden patterns in data. Data miners are interested in finding useful relationships between different data elements, which is ultimately profitable for businesses.
Data mining
Data mining is also known as Knowledge Discovery in Data (KDD). As mentioned above, it is a field of computer science, which deals with the extraction of previously unknown and interesting information from raw data. Due to the exponential growth of data, especially in areas such as business, data mining has become very important tool to convert this large wealth of data in to business intelligence, as manual extraction of patterns has become seemingly impossible in the past few decades. For example, it is currently been used for various applications such as social network analysis, fraud detection and marketing. Data mining usually deals with following four tasks: clustering, classification, regression, and association. Clustering is identifying similar groups from unstructured data. Classification is learning rules that can be applied to new data and will typically include following steps: preprocessing of data, designing modeling, learning/feature selection and Evaluation/validation. Regression is finding functions with minimal error to model data. And association is looking for relationships between variables. Data mining is usually used to answer questions like what are the main products that might help to obtain high profit next year in Wal-Mart?
Query Tools
Query Tools are tools that help to analyze the data in a database. Usually these query tools have a GUI front end with convenient ways to input queries as a set of attributes. Once these inputs are provided the tool generates actual queries made up of the underlying query language used by the database. SQL, T-SQL and PL/SQL are examples of query languages used in many popular databases today. Then, these generated queries are executed against the databases and the results of the queries are presented or reported to the user in an organized and clear manner. Typically, the user does not need to know a database-specific query language to use a Query tool. Key features of Query tools are integrated query builder and editor, summery reports and figures, import and export features and advanced find/search capabilities.
What is the difference between Data mining and Query Tools?
Query tools can be used to easily build and input queries to databases. Query tools make it very easy to build queries without even having to learn a database-specific query language. On the other hand, Data Mining is a technique or a concept in computer science, which deals with extracting useful and previously unknown information from raw data. Most of the times, these raw data are stored in very large databases. Therefore Data miners can use the existing functionalities of Query Tools to preprocess raw data before the Data mining process. However, the main difference between Data mining techniques and using Query tools is that, in order to use Query tools the users need to know exactly what they are looking for, while data mining is used mostly when the user has a vague idea about what they are looking for.