What is Data Mining and Data Warehousing?

• In this article you will learn:
• 1.What is Data warehouse?
• 2.What Is Data Mining?
• 3.Difference between Data Mining and Data Warehouse.
• 4.Why use Data Warehouse?
• 5.Why use Data mining?
• 6.Advantages of Data Warehousing.
• 7.Disadvantages of a Data Warehousing.
• 8.Advantages of a Data Mining.
• 9.Disadvantages of Data Mining.
• 10.Conclusion.

What is a Data warehouse?

A data warehouse is a way to store and organize data from many different sources so that it can be used to make business decisions. It is a mix of technologies and parts that make it possible to use data in a strategic way.Data Warehouse is a place where a business stores a lot of information electronically so that it can be queried and analyzed instead of being used to process transactions. It is the process of turning data into information and giving that information to users so they can analyze it.

What Is Data Mining?

Data mining is the process of looking through large sets of data for hidden, valid and possibly useful patterns. Data mining is all about finding connections between pieces of data that you wouldn’t have thought of before.It is a skill that comes from many different fields and uses machine learning, statistics, artificial intelligence and database technology.Data mining can be used to find out things that can be used for marketing, finding fraud, making scientific discoveries etc.

Difference between the Data Mining and Data Warehouse:

Data Mining	Data Warehouse
Data mining is a process of analyzing unknown patterns of a data.	A data warehouse is a database system which is designed for an analytical instead of a transactional work.
Data mining is the process of comparing a lot of information to look for patterns.	Data warehousing is the process of putting all of the information from different sources into one place.
Data mining is usually done by a business users with assistance of engineers.	Data warehousing is the process which needs to occur a before any data mining can take place.
Data mining is a considered as a process of extracting data from a large data sets.	Data warehousing on the other hand is the process of putting all the important data in one place.
One of the best things about data mining techniques is that they can find and point out errors in a system.	One of the good things about Data Warehouse is that it can be updated regularly. So it’s perfect for a business owner who wants the best and most up-to-date features.
Data mining helps to create a suggestive patterns of important factors. Like buying habits of customers, products, sales. So that companies can make a necessary adjustments in operation and production.	Data Warehouse adds a extra value to operational business systems like a CRM systems when a warehouse is integrated.
Data mining techniques are never 100% accurate and sometimes they can have very poor outcomes.	In a data warehouse there is great chance that the data which was be required for analysis by an organization may not be integrated into a warehouse. It can easily lead to loss of an information.
The information gathered based on a Data Mining by organizations can be misused against the group of people.	Data warehouses are created for the huge IT project. Therefore it involves high maintenance system which can impact a revenue of medium to be small-scale organizations.
After a successful initial queries users may ask more complicated queries which would increase a workload.	Data Warehouse is a complicated to implement and maintain.
Organizations can benefit from this analytical tool by an equipping pertinent and usable knowledge-based information.	Data warehouse saves a large amount of historical data which helps users to analyze various time periods and trends for making a future predictions.
Organizations need to spend a lots of their resources for training and Implementation purpose. Moreover Different algorithms were used to make different data mining tools work in different ways.	In a Data warehouse data from many different places are put together. The information needs to be cleaned up and changed in some way. This might not be easy.
The data mining methods are more cost-effective and efficient compares to the other statistical data applications.	Data warehouse’s responsibility is to simplify every type of a business data. Most of the work that will be a done on user’s part is inputting a raw data.
Another critical benefit of a data mining techniques is an identification of errors which can lead to losses. Generated a data could be used to detect a drop-in sale.	Data warehouse allows the users to access critical data from a number of sources in a single place. Therefore it saves user’s time of retrieving a data from multiple sources.
Data mining helps to generate an actionable strategies built on a data insights.	Once input any information into a Data warehouse system will unlikely to lose track of this data again. need to conduct a quick search helps to find a right statistic information.

Why use a Data Warehouse?

• Adds more sources of data and helps a production system handle less stress.
• Optimized Data for reading access and disc scans that come one after the other.
• Data Warehouse helps to keep data safe from changes to the source system.
• Allows the users to manage their master data.
• The data in the source systems should be made better.

Why use a Data mining?

• Figure out what the data mean and how they relate to each other. Use this information to come up with money-making ideas.
• Businesses can make decisions quickly that are based on facts.
• Helps to figure out why people shop in grocery stores in strange ways.
• Optimize your website’s business by giving each visitor a unique offer.
• Used in business marketing to figure out how often a customer responds.
• For marketing purposes making and keeping track of a new customer group.
• Predict customer defections such as which customers are most likely to switch to a different supplier soon.
• Figure out which customers are profitable and which ones are not.
• As part of the process of finding fraud look for any kind of strange behavior.

Advantages of Data Warehousing:

• The job of the data warehouse is to make it easier to understand any kind of business data. The user will spend most of his or her time entering raw data.
• One of the best things about this technology is that it can be updated constantly and often.
• Because of this data warehouses are great for businesses and entrepreneurs who need to keep up with their customers and target audience.

Disadvantages of a Data Warehousing:

• There is a big chance of collecting data that is not useful or relevant.
• The other things that could go wrong are data loss and deletion.
• In a data warehouse data from many different places are put together.
• The data needs to be cleaned up and changed in some way.
• This could be a hard thing to do.

Advantages of a Data Mining:

• Data mining helps with many different kinds of data analysis and sorting. One of the best things that can be done here is to find and fix any unwanted problems in the system. This method makes it easier to get rid of any risks faster.
• Compared to other ways to use statistical data data mining methods are both the most cost-effective and effective.

Disadvantages of Data Mining:

• Data mining isn’t always accurate and if it’s done wrong, it can cause data breaches.
• Organizations must spend a lot of money on training and putting their plans into action. Also the algorithms that are used to make data mining tools make them work in different ways.

Conclusion:

A data warehouse is made to help with management while data mining is used to find useful information and patterns in large amounts of data. The process of putting information into the data warehouse is called “data warehousing.