# Learn Difference Between Data Mining And Data Warehouse | Full Guide! **URL:** \ **Category:** Tutorials & Methods\ **Tags:** data-recovery\ **Created:** [November 1, 2019, 11:29pm UTC](https://onehack.st/t/learn-difference-between-data-mining-and-data-warehouse-full-guide/61548 "2019-11-01T23:29:51Z")\ **Posts on this page:** 2\ **Page:** 1
**Author:** ![Aina](https://onehack.st/user_avatar/onehack.st/aina/32/167469_2.png) [@Aina](https://onehack.st/u/Aina)\ **Post date:** [November 1, 2019, 11:29pm UTC](https://onehack.st/t/learn-difference-between-data-mining-and-data-warehouse-full-guide/61548/1 "2019-11-01T23:29:51Z")
## What is Data warehouse? A data warehouse is a technique for collecting and managing data from varied sources to provide meaningful business insights. It is a blend of technologies and components which allows the strategic use of data. Data Warehouse is the electronic storage of a large amount of information by a business that is designed for query and analysis instead of transaction processing. It is a process of transforming data into information and making it available to users for analysis. _(Source: guru99)_ ## What Is Data Mining? Data mining is looking for hidden, valid, and potentially useful patterns in huge data sets. Data Mining is all about discovering unsuspected/ previously unknown relationships amongst the data. It is a multi-disciplinary skill that uses machine learning, statistics, AI and database technology. The insights extracted via Data mining can be used for marketing, fraud detection, and scientific discovery, etc. ![image](https://onehack.st/uploads/default/original/3X/0/c/0c7f84ff44b4b8238b3c3da567cd3e81b607151a.jpeg) ## Data Mining Vs Data Warehouse: Key Differences | **Data Mining** | **Data Warehouse** | | --- | --- | | Data mining is the process of analyzing unknown patterns of data. | A a data warehouse is a database system which is designed for analytical instead of transactional work. | | Data mining is a method of comparing large amounts of data to finding right patterns. | Data warehousing is a method of centralizing data from different sources into one common repository. | | Data mining is usually done by business users with the assistance of engineers. | Data warehousing is a process which needs to occur before any data mining can take place. | | Data mining is considered as a process of extracting data from large data sets. | On the other hand, Data warehousing is the process of pooling all relevant data together. | | One of the most important benefits of data mining techniques is the detection and identification of errors in the system. | One of the pros of Data Warehouse is its ability to update consistently. That’s why it is ideal for the business owner who wants the best and latest features. | | Data mining helps to create suggestive patterns of important factors. Like the buying habits of customers, products, sales. So that, companies can make the necessary adjustments in operation and production. | Data Warehouse adds an extra value to operational business systems like CRM systems when the warehouse is integrated. | | The Data mining techniques are never 100% accurate and may cause serious consequences in certain conditions. | In the data warehouse, there is a great chance that the data which was required for analysis by the organization may not be integrated into the warehouse. It can easily lead to loss of information. | | The information gathered based on Data Mining by organizations can be misused against a group of people. | Data warehouses are created for a huge IT project. Therefore, it involves a high maintenance system which can impact the revenue of medium to small-scale organizations. | | After successful initial queries, users may ask more complicated queries which would increase the workload. | Data The warehouse is complicated to implement and maintain. | | Organisations can benefit from this analytical tool by equipping pertinent and usable knowledge-based information. | Data warehouse stores a large amount of historical data which helps users to analyze different time periods and trends for making future predictions. | | Organisations need to spend lots of their resources for training and Implementation purposes. Moreover, data mining tools work in different manners due to different algorithms employed in their design. | In Data warehouse, data are pooled from multiple sources. The data needs to be cleaned and transformed. This could be a challenge. | | The data mining methods are cost-effective and efficient compares to other statistical data applications. | Data warehouse’s responsibility is to simplify every type of business data. Most of the work that will be done on the user’s part is inputting the raw data. | | Another critical benefit of data mining techniques is the identification of errors which can lead to losses. Generated data could be used to detect a drop-in sale. | Data the warehouse allows users to access critical data from the number of sources in a single place. Therefore, it saves the user’s time of retrieving data from multiple sources. | | Data mining helps to generate actionable strategies built on data insights. | Once you input any information into the Data warehouse system, you will unlikely to lose track of this data again. You need to conduct a quick search, helps you to find the right statistic information. | ## Why use Data Warehouse? Some most important reasons for using Data warehouse are: - Integrates many sources of data and helps to decrease stress on a production system. - Optimized Data for reading access and consecutive disk scans. - Data Warehouse helps to protect data from the source system upgrades. - Allows users to perform master Data Management. - Improve data quality in source systems. ## Why use Data mining? Some most important reasons for using Data mining are: - Establish relevance and relationships amongst data. Use this information to generate profitable insights - Business can make informed decisions quickly - Helps to find out unusual shopping patterns in grocery stores. - Optimize website business by providing customize offers to each visitor. - Helps to measure customer’s response rates in business marketing. - Creating and maintaining new customer groups for marketing purposes. - Predict customer defections, like which customers are more likely to switch to another supplier in the nearest future. - Differentiate between profitable and unprofitable customers. - Identify all kind of suspicious behavior, as part of a fraud detection process. ## Summary: - A data warehouse is a blend of technologies and components which allows the strategic use of data. It is a process of centralizing data from different sources into one common repository. - Data mining is looking for hidden, valid, and potentially useful patterns in huge data sets. - Data Warehouse helps to protect data from the source system upgrades. - Data warehouses are used by data scientists, business intelligence developers, to analyze data. - Data mining technology helps businesses to reach closer to their objectives. ## ENJOY & HAPPY LEARNING! ✌ ---
**Author:** ![Stain\_Stephen](https://onehack.st/user_avatar/onehack.st/stain_stephen/32/18549_2.png) [@Stain\_Stephen](https://onehack.st/u/Stain_Stephen)\ **Post date:** [November 2, 2019, 2:32am UTC](https://onehack.st/t/learn-difference-between-data-mining-and-data-warehouse-full-guide/61548/2 "2019-11-02T02:32:28Z")
nice topic