Introduction to data mining and data warehousing | Advantages

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Today everyone is using the Internet effectively in everyday life. We can say that it is no longer possible to do any of our work without internet, due to its increasing trend, everyone uses it and consumes a lot of data. In this article, we will read Introduction about Data Warehouse and Data Mining.

introduction to data mining and data warehousing

Introduction to data mining and data warehousing

So let’s first understand what is data mining ?

What is data mining ?

It is a process in which data is analyzed and patterns, trends, useful data are found in the data, then it is performed or executed. If some useful information is obtained in the data, then the process of data mining is implemented for this.

This process uses artificial intelligence, statistics and computer graphics. The organization solves its problem using the process of data mining.

Rules of Data mining :-

There are some rules in the process of data mining, which we call association rules. These rules are mainly used to analyze the data. We understand this through some process. 

  • Path analysis
  • Classification
  • Clustering
  • Forecasting

Path analysis :-

In this, we first understand the path of the data, then after that the details about the data are extracted.

Classification :-

After applying the path analysis process, we classify the data in the classification process.

Clustering :-

When the data is classified, then the process of clustering is applied. Clustering means merging data from one to another.

Forecasting :-

Forecasting as the name indicate Forecasting is used to predict data, what type of data are used by user.

Example of data mining :-

  1. If you are a buyer or customer who carries out similar purchases through your credit card or online banking, then the company providing the credit card or online banking service understands the behavior of its customer product marketing. This company analyzes the data to buy the products of its customers, which type of products our customers are buying, understand the market pattern so that this company can provide new types of promotions and new types of deals.

2. If you do online shopping, such as through an online e-commerce website, then you must have seen that the same type of advertisement you see in Google and YouTube.

Application of Data mining :-

  • Anamoly detection
  • Dependency Modeling
  • Clustering

Anamoly detection :-

In this process, by mining the data, useful data is sorted in it, which we can use in other types of service.

Dependency Modeling :-

In this we find a lot of information inside the data variable. for example :- super market shopping details of consumers.

Clustering :-

In this, the data is sorted, then it is combined with other useful data.

Advantages :-

  1. Through data mining, we sort out the patterns, trends and useful data in the data that this data is used for other purposes.
  2. Through data mining, we can increase sales of any product.
  3. Data mining increases the decision making capability of any organization.
  4. it can be easily analyze the big data and it make useful for another purpose.
  5. Data mining easily increase the system performance ability.

Disadvantages :-

  1. Data mining lose the security analyze of any system.
  2. We cannot say that data mining is accurate, it is variable and sometimes the data is incomplete.
  3. While mining data, such data also comes which is of no use means some data is unusable.
  4. There are many software is difficult to apply the process of data mining.
Data mining used

Now we will talk about the question that are maximum times ask.

           What is data mining in simple terms ?

Ans. :- Data mining is a process in which you sort your useful data into a lot of data and use it for your various tasks like business growth, analysis the customer behavior , data analysis.

           What is data mining used for ?

Ans. :- A data mining used for various purpose like :-

  1. Artificial Intelligence
  2. Big data process
  3. Corporate sectors
  4. Educational department
  5. Analyze market strategies.

           What is best software or tools for data mining ?

  1. Rapid miner
  2. Weka
  3. Orange
  4. Knime
  5. Rattle
  6. Tanagara
  7. XL miner

After understanding “Introduction about data mining” we will understand “data warehouse”.


What is Data warehouse :-

The Data warehouse is made up by two words Data and Warehouse.

Lets first understand what is data ?

Data :-

 Any information that we get through the computer’s execution process is called data. Basically data are represented by different numbers, alphabets, alphanumeric, special symbols (+,- ,* ,/ ,& ,% ,$ ,#). 

Data is of no use in its form (alphabets, alphanumeric, special symbols). But when we process and interpret the same data, then the correct meaning of them comes out, and which are very useful for us. These processed data are also called information.

Warehouse :- 

This means securing and storing any data so that it can later be used for data analysis, business purpose.

There is a data store in the data warehouse, due to which we can use the data anytime. It has been seen many times that in the data warehouse, store data is used for organization marketing, product sales, development.

Example :- Data analyst, Data scientist.

Data warehouse increase the security of data and it is used for data mining and data analysis. Data warehouse is also known as Enterprise Data warehouse.

Features :-

There are many features of Data Warehouse which we will understand one by one.

Subject Oriented :-

A data warehouse can be built for any subject, hence it is also called oriented. Meaning that we can do research and data analysis related to any subject in it.

Integrated :-

In data warehouse we can easily separated the data for different purpose.

Advantages of Data warehouse :-

  1. Data warehouse is mostly used for developing the business model like marketing, manufacturing, sales etc.
  2. The data warehouse is increased system performance and also its ability.
  3. The data quality is also increased.
  4. Data warehouse increasing decision making capability of any organizations, data scientist.

Disadvantages of Data warehouse :-

  1. Data warehouse estabilization cost is not for beneficial purpose.
  2. Data warehouse process taking more times for giving results.
  3. It is hard to manage and not easy way to handle.

best tools for data warehousing

Tools are used for Data warehouse :-

There are different types of software and tools are available for data warehouse :-

  1. Cloudera
  2. Maria DB
  3. Amazon Redshift
  5. Teradata
  6. Postgre SQL
  7. Mark Logic
  8. Exadata
  9. Microsoft azure
  10. Google big query.

So guys You will must all understands the Introduction to Data mining and Data warehousing. If you have any query about this topic then please comments.




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