Application of Data Warehousing and Data Mining

Application of Data Warehousing and Data Mining

Data Warehousing

The process of constructing and using a data warehouse is called Data Warehousing, where a data warehouse is a subject oriented, integrated, time variant and non-volatile collection of data and it provides consolidated data in multi-dimensional view.

 Data warehouse also provides Online Analytical Processing tools (OLAP),thus helping in effective analysis of data in multi-dimensional space.

Applications of Data Warehousing

Data Warehousing can be used in

1.     Financial Services:  Data Warehousing plays an important role in Financial Services where it includes Financial services risk analysis, Credit cards and Fraud detection.

2.     Business: In Business, we can use Data Warehousing for trade sales and claims analysis, customer care and public relations, shipment and inventory control, Trend analysis, Buying pattern analysis, Pricing policy, Inventory Control, Sales promotions, Optimal distribution channel.

3.     Transport: We can use Data Warehousing in Transport to collect the information of vehicles and also their management.

4.     Telecommunication Services: It includes call flow analysis and customer profile analysis, New product and Service productions, Reduction of IS budget, Profitability analysis.

5.     Health care services: In hospitals, patient admission and discharge analysis,  book keeping in accounts departments and Reduction of operational expense.

6.     Banking Services: In Banking, Data Warehousing can be used in financial decision making, target marketing, selecting better marketing partners, mortgage loan portfolio, identifying new customers and customer segmentation.

7.     Government and Education: In Government applications data warehousing is used in auditing tax records for patterns, justice resource deployment and provider care adequacy.

In Education, It can be used for Student demographics, course scheduling, University finances.

8.     Insurance: It helps in maintaining accurate and consolidated view of customer portfolios. It also helps in collecting and analysing claims information, utilization and Government reporting, Risk management, Market movement analysis and Customer tendencies analysis.

9.     Airline: Data Warehousing can be used in Airline to provide Crew assignment, Aircraft development, Mix of fares, Analysis of route profitability and frequent flyer program promotions. 

10.   Banking: In Banking, Data Warehousing can be used for Customer Service, Trend Analysis, Product and Service promotions, Reduction of IS expenses.  

11.  Personal Care: It includes Distribution decisions, Pricing policy, Sales decisions, Product promotions.

12.  Public Sector: One of the major applications of Data Warehousing is that it can be used in Public sector for Intelligence gathering.

Data Mining

The process in which raw data is converted into useful information by using software by looking patterns in large batches of data is referred as Data Mining.

Data Mining Applications

Various applications of Data Mining are as follows

1.     Financial Data Analysis: It is used in banking and financial industries which facilitate high quality systematic data analysis and data mining.

Some of the illustrations are given below:

a.     Construction of Data warehouses for multi-dimensional data analysis and data mining.

b.     Prediction of Loan Payment and customer credit policy analysis.

c.      Classification and grouping of customers for targeted marketing.

d.     Detection of fraud and financial crimes.

2.     Retail Industries: Data mining is used in the collection of large amount of data which includes customer purchasing history, sales, consumption, transportation of goods and services.

       The quantity of collected data rapidly increases as the ease and availability of web increases.

       Examples of Data Mining in Retail industries

a.     Multidimensional analysis of customers, products, region and time.

b.     Customer Retention

c.      Product recommendation and cross-referencing of items.

3.     Telecommunication Industry: Helps in identifying the telecommunication patterns to detect fraud activities and improve Quality of Service(QoS).

        Some of the examples of applications of Data Mining in telecommunication Industry

a.     Identification of fraud and unusual patterns.

b.     Sequential pattern analysis.

c.      Mobile telecommunication services.

4.     Biological Data Analysis: Biological data mining is highly applied in the field of Bio informatics.

        Some examples are,

a.     Analysis of genetic networks and protein pathways

b.     Visualization tools in genetic data analysis

5.     Intrusion detection: The counter measures to avoid intrusion includes information protection and user authentication.

        Some examples are,

a.     Analysis of stream data

b.     Distributed data mining

c.      Visualization and query tools

6. Health care: Data mining uses data and analytics to improve care and reduce cost.

It can also help health care insurers to detect abuse and makes the patients receive appropriate care.

7. Education:   Data mining in educational field is called Educational data mining which focuses on developing methods that discover knowledge in educational environments.

Learning pattern of students can be analysed and helps the   institution to take accurate decisions and predict the results of the students.

8. Criminal Investigation: The huge volume of crime data sets can be maintained by applying data mining.Text based crime reports can be converted into word processing files which helps in crime matching process.

9.  Market Segmentation: Data Mining plays an important role in Market Segmentation where it can identifies the common characteristics of customers who buys the same product from the company.

10. Customer Churn: Data Mining can also be useful in predicting the customers who are likely to leave one company and go to another company.

11. Direct Marketing: In Direct marketing, data Mining can be useful to identify which prospectus should need to be included in mailing list to obtain highest response rate.

12.  Trend Analysis: It helps to identify the trend of the customer from one month and in the next month.

13.  Science: Data Mining also plays an important role in Science and Technology as it can be used to simulate Nuclear explosions and also in visualizing quantum Physics.

14. Manufacturing: In Manufacturing field, data Mining can be used for Optimizing product design, Balancing manufacturability and safety, Machine utilization and improving shop floor scheduling.

15. Oil and Gas: Data Mining can be used for Prioritizes drilling locations, Simulates underground flows to improve recovery and to analyze the seismic data for signs of underground deposits.

Thus Data Mining is an important field which can be used in various other applications like Research analysis, Corporate Surveillance, Customer Segmentation, Customer Relationship Management, Medicine, Entertainment, and so on.

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