Difference between data mining and data warehousing pdf

All these technologies support functions like data extraction, data transformation, data storage, providing user interfaces for accessing the data. Data warehouse is not a product or software, it is an informational environment, which provides information like an integrated view of an enterprise.

It supports transactions made for decision making without affecting operational systems. It is a flexible resource to obtain strategic information. Data Mining can be done only when there is a well integrated large database i.

So data warehouse must be completed before data mining. Data warehouse must have information in well-integrated form so that data mining can extract the knowledge in an efficient manner. Your email address will not be published. Key Differences Between Data Mining and Data Warehousing There is a basic difference that separates data mining and data warehousing that is data mining is a process of extracting meaningful data from the large database or data warehouse.

However, data warehouse provides an environment where the data is stored in an integrated form which ease data mining to extract data more efficiently. Leave a Reply Cancel reply Your email address will not be published. In this process, the analysis is done by the computer itself using above mentioned techniques to draw out relevant insights and inputs from it.

Predictive analysis can also be carried out with data mining in order to analyze what the future consequences of any current happening might be. Without data mining, it is not possible to even see or think of such analysis or relations between the different sets of data.

Hence, data mining is majorly used for identifying and drawing out hidden relationships between the data. Data mining is also referred to as Knowledge Discover in Database KDD where diverse data mining tools and machine learning systems are used for deriving something useful out of just a data.

Data mining foretells the anticipated consequences and gives a clear idea of what kind of actions to take. It deals with large sets of data and huge databases. Trend analysis, market analysis, fraud detection, financial analysis, existing trends, all can be gathered from data mining.

It helps businesses to drive to well informed decisions and strategies so that further losses or errors can be prevented. Data mining is an economical way of generating analysis or reviews rather than other statistical data application techniques. Tag: comparison. I am Rashmi Bhardwaj. I am here to share my knowledge and experience in the field of networking with the goal being - "The more you share, the more you learn.

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Popular Course in this category. Course Price View Course. Free Data Science Course. Login details for this Free course will be emailed to you. Email ID. Contact No. It is a process which is used to integrate data from multiple sources and then combine it into a single database. It is the process which is used to extract useful patterns and relationships from a huge amount of data. Data mining techniques are applied on data warehouse in order to discover useful patterns.