Difference Between Data Mining and Data Warehousing

Data mining and warehousing for any hope approved in global or national level organization are two essential process.Both techniques to help prevent fraud and improve management statistic data and ranking.Data mining is used to rely on data collected in the data warehouse phase to detect important mode.

Data mining and data warehouse are considered part of the data analysis.But they work in different ways.This blog will discuss the differences between the two,And whether one can exist in the absence of another.

数据挖掘　　

Involved in the large data set and find data mining model.It is a subset of the data used in the fields of science,包括营销、Finance and engineering.Data mining can be done manually,Can also be done using automation system.像HadoopThe open source software framework allows you to store、Access and manage your data.

Data mining using artificial intelligence software to view a large amount of data.它使用 机器学习算法 With the passage of time analysis of sales figures,以发现数据中的模式.然后,They according to the model to predict future events.

Although machine learning algorithms is complicated,But compared with the algorithm training,Deployment model is a simple process.Deployment model related to transform the model into different formats and loads it into expected machine fine process.

Many popular machine learning algorithm using the migration study.This means that you can be in any system deployment model.Continuous deployment to allow devices to each new model to study mode and its.

More and more industries are finding ways to use data mining functions.数据挖掘包括3个阶段：数据准备、模型构建、验证和部署.These functions allow to collect and analyze information to make better decisions and policy.

Some companies record and analyze customer information,While other companies to use data mining tools to analyze trends.例如,Some companies may decide to mining data from the user,In order to determine which products they should sell.

By mining the data and trend analysis,They can see what products are very popular,And make more products,Ensure that they meet the needs of customers.Data mining tools is a good way to collect and analyze data.

数据仓库　　　　

Data warehouse data is stored in one place,So that more people can access、Share and use it.A data warehouse based on relational database management system (RDBMS).It is for the purpose of the data structure to form,And the user can easily query them.

The data warehouse to store all your company's related business information.例如,The customer's name and address、They are under each order of product information or by the month sales data.

A good example is Google search console.It allows you to cross multiple dimensions analysis of your site's performance.These dimensions include traffic sources、User behavior patterns, etc.

RDBMSTrack each row in the table all the changes.If you are one of the edit or insert new records in the table,All other copies will automatically reflect these changes.

Data warehouse is mainly divided into three types,Each has its different functions：

1.Sales and Marketing Department to use the data mart data collected from customers and commentators sources.

2.企业数据仓库 Is combined with the centralized database of all departments within the organization.They are the core of the decision support system.

3.Operational data store contains the user data and updated frequently.They are effective to people.

区别

数据挖掘 数据仓库　　

By using data mining research records and trends to find specific data By creating an efficient and accurate data available to all divisions of the company warehouse,Minimize the need for data input

Data mining enables you to quickly make a wise decision 建立一个安全、可靠、Extensible and is available for all people to access the central data repository.

It is hard to find before a good way to solve the business problem the answer It in a structured、易于访问、Maintain and update the format of the information

Can also be used to forecast analysis and forecast Building data warehouse is appropriate for your business needs,Helps you to efficiently manage data

The model accuracy is not high.Model may not be able to view the data in the same way as with human More data push up storage costs.When the company has more data than it can store data,这可能会成为一个问题

在数据挖掘中,A lot of time requirement can be attributed to the fact that there are many steps in the process of The processing of the data warehouse is not fast.Data is stored in the repository will significantly slow down the access time

Can at any time of any data access data set Only the summary table of the data warehouse is available,Detailed data is not available.If you want to analyze accurate data,Not just the summary data,这是一个问题

Can use different visualization tools andPythonLibrary for advanced analysis. In the data warehouse can't advanced data analysis,Because the information is no longer available in its original form.

结语　　

在这两种情况下,You need to store your information,So that need access to the rest of it（Or if you work alone or don't trust anyone else）可以访问它.

The process of data mining and warehousing are two different,But they have some similarities.Both are related to view the large data set and found in the data set mode.Data mining with an eye to the whole data set,The data warehouse should focus on a subset of the data sets,For example, a single customer record or department sales report.

Data mining and data warehouse has many advantages.Data mining can help organizations to identify patterns and trends in the data,从而做出更好的决策.Data warehouse can help organizations more efficiently store and organize data,Make it easier to access and use.

Time requirements is also due to the large amounts of data availability.This can lead to the complexity of the model,Because the model must be able to handle all data.Data mining and warehousing can help organizations to improve efficiency and effectiveness.