MODEL INTEGRATION E COMMERCE AND DATA MINING:Callenges faced and architecture

Data Mining tools discover the pattern from data stored in data warehouse.Any e commerce application is highly depend on data mining.Also their are many factors that are responsible for the success of data mining like database is rich of data,electronic collection provide only ,meaningful data,ROI can be measured very easily.To tale real advantage of this data mining should be properly integrated with e commerce application with appropriate data transformation strategy from the transaction processing system used for inputting the data into data warehouse and vice versa.

Integrated Architecture
 Their are three major component in this architecture
1.Data Defination according to business
2.Customer interface
3.Data analysis
Connecting these three component we require three bridge
1.Data stage transfer
2.Build data warehouse
3.Display Result

Challenges faced
Their are some major challeges faced while integration
1.Comprehensive data mining result
2.Data mining process accessibility
3.Detect robots and Crawlers
4.Handle Large amount fo data
5.Multiple Granularity level
6.Handle date and time  

Evaluation parameter for pre built datawarehouse

Their are number of predefined data warehouse available in the market ,but before buying their are some factor which need to be considered and evaluated throughly.It is necessary to identify their advantages and disadvantages of each .Firstly organization need to evaluate their need and requirement of module,then based on that you need to judge the warehouse which  suits to your organization

There rare many criteria need to considered before finalize your data warehouse:-
1.Operational time-In how much time your datawarehouse will be operational?
2.Databased module used in the architecture of datawarehouse
3.Stability : Whether your stable foe longer period?
4.Metadata: It is important to see the quality of meta data used
5.Reports and analytics: It is important to see the analytic power and different type of reporting technique used  in the datawarehouse
6.Real time updating facility: check whether real time updation facility is available or not
7.ERP performance-check the erp performance on that datawarehouse
8.Service offering-See ad don facility available are beneficial to you or not
9.Technical requirement-Check the hardware requirement because it affect the overral cost directly
10.Maintenance and on line support available or not

Data WareHouse: Whether you Buy or Buit It?

It is very difficult for the organization to decision on data warehouse. In market many data ware house is readily available , but does not fulfill your requirement
In general their are 3 choices available to obtain a datawarehoue
1.Buy it
2.Built it according to our requirement
3.Create a custom warehouse
The easier way is to buy a warehouse from market like IBM,Oracle,SAP etc ,number of option are available.The advantage of this is time saving.So it is important to check the application before buying it .
Sometime,rather to buy data warehouse fully buy a custom and reframe it accordingly.This approach involves less time,less cost and less risk than fully purchase data ware.Theoretically framework customize your need, doing this is not always easy,less expensive and fool proof.Success depend on skill and experience you have in customization.Maintenance and support is one of the major problem with framework.So never recommend the friend to go for built in option because it is very expensive,require lot of man power and many other factor influencing it.

Is a Data Warehouse really necessary?

The data needed to provide reports, dashboards,analytic applications and ad hoc queries all exists
within the set of  applications that support your organization. Rather to use all those applications separately Why not just use one of the Business Intelligence  tools to obtain it directly? 

BI pioneers have discovered the hard way that the “direct access” approach simply does not work very well. There is no reason to add the name of your organization to the long list of failures. Some of the many reasons why direct connection almost never works include:

New releases of application software frequently introduce changes that make it necessary to rewrite and test reports.

• These changes make it difficult to create and maintain reports that summarize data originating within more than one release.
• Field names are often hard to decipher. Some are just meaningless strings of characters.
• Application data is often stored in odd formats such as Century Julian dates and numbers
• without decimal points.
• Tables are structured to optimize data entry and validation performance, making them hard to use for retrieval and analysis. 
• There is no good way to incorporate worthwhile data from other sources into the database of a
• particular application.
• Developing and storing metadata is an awkward process without a data warehouse – there is no  obvious place to put it.
• Many data fields that users are accustomed to seeing on display screens are not present within the database, such as rolled-up general ledger balances.
• Priority always needs to be given to transaction processing. Reporting and analysis functions tend to perform poorly when run on the hardware that handles transactions.
• There is a risk that BI users might misuse or corrupt the transaction data.
• There are many ways in which BI users can inadvertently slow the performance of applications.

Relationship between Data Warehousing and Business Intelligence

The process, technologies, and tools required to turn data into information, information into knowledge, and knowledge into wisdom that excel the
profitable business decision.
Business intelligence integrate data warehousing, various business analytic tools, and  knowledge management to give addons to the business in various aspect

Why You Need a Data Warehouse

Building data warehouses is very difficult process . Many early adopters found it to be costly, time taking, and resource consuming. Over the years, it has earned a reputation that this was very risky process. This is especially true for those who have tried to build data warehouses themselves without the help of experts.

Fortunately, it is usually no longer necessary to custom build your own data warehouse. Pre built solutions are now available that drastically reduce the effort and risk. As a result, the time has come for organizations to develop a thorough understanding of data warehousing.
Managing Business  and handling  different market seniero without making use of information technology is difficult now a days
So to make life easy for managers of the organization or to make good market strategy we require large amount of data so that micro level research analysis will be done and by this we can increase the decision making power of the managers
Here Data warehousing is a tool very useful which can store huge amount of data in three dimensional form

Why Data is so Important to E Governance?

Modern day businesses handle and process homongenous amounts of data, which can be gathered either in-house or from external sources. With the advent of internet, web, and mobile devices the main challenge of the decade is to manage this huge resource of unstructured or raw data, which is getting generated every moment at a very fast pace. Unstructured data streams rapidly and constantly from different sources and is heterogeneous and variable in format. Unstructured data comprise of all data flowing in from customer interactions on websites, marketing applications running on websites, social networks, e-commerce sites, blogs, and responses from surveys and feedback. This data can be dug into and used to uncover customer consumption patterns, product and brand preferences, and other information which queries and reports can’t effectively reveal. So even with an investment of time and money, it is necessary to store and harness this huge volume of data efficiently. This has given rise to the importance of data warehousing and data mining.

1 . INTRODUCTION

E-governance involves the application of Information and Communication Technologies by government agencies for information and service delivery to citizens, business and government employees. It is an emerging field, faced with various implementation problems related to technology, employees, flexibility and change related issues, to mention a few. Global shifts towards increased deployment of IT infrastructure by governments emerged  with the advent of the World Wide Web. With the increase in Internet and mobile connections, the citizens are learning to exploit their new mode of access in wide ranging ways. They have started expecting   more and more information and services online from governments and corporate organizations to enhance their civic, professional and personal lives .The concept of e-governance come into existence in India during the seventies with a focus on development of government applications in the areas of defense, economic monitoring, planning and the inclusion of Information Technology to manage data intensive functions related to elections, census, tax administration etc. The role & efforts made by National Informatics Center (NIC) to connect all the district headquarters during the eighties was a very new innovative approach .

From the early nineties, IT technologies were supplemented by ICT technologies to extend  its use for wider  applications with policy implementation & emphasis on reaching out to rural areas and taking in greater inputs from NGOs and private sector. There has been an increase involvement of international agencies under the framework of e-governance for development to catalyze the development of e-governance laws and technologies in developing countries. For governments, the motivation to shift from manual processes to IT-enabled processes may be increased efficiency in administration and service delivery, but this shift can be conceived as a worthwhile investment with potential for returns.

E-governance is the process of service delivery and information dissemination to citizens using electronic means providing the following benefits over the conventional system

 • Increased efficiency in various Governmental processes

 • Transparency and anti corruption in all transactions

 • Empowerment of citizens and encouragement of their participation in governance.

The main objective of E-Governance is to change organization into e-organization. An e-organization needs to focus on the following things:-

           

1. develop customer orientation
2.  manage customer relationships
3. streamline business processes
4. communicate better
5. organize information
6. work more flexibly
7. make better decisions.

ü  coordinate activities better

E-governance is the application of information & communication technologies to transform the efficiency, effectiveness, transparency and accountability of informational & transactional exchanges with in government, between govt. & govt. agencies of National, State, Municipal & Local levels, citizen & businesses, and to empower citizens through access & use of information. Governments deal with large amount of data. To ensure that such data is put to an effective use in facilitating decision-making, a data warehouse is constructed over the historical data. It permits several types of queries requiring complex analysis on data to be addressed by decision-makers.

This Paper deals with scope and use of data warehousing & Data mining in all the dimensions of e-governance like Government to Citizen (G2C) Citizen to Government (C2G) Government to government (G2G) Government to Business ,Government to NGO (G2N).Their are many methodology used to increase the efficiency of E-governance .Three complimentary trends are Data warehousing, OLAP ,Data mining. By using these technique we find that data warehousing is very  helpful in analyzing Current & Historical data finding useful pattern & support decision strategies .OLAP is useful in solving complex queries & views , interactive online analysis of data .Using Data mining technique & algorithm, automatic discovery of pattern & other interesting trends are find out

Keywords: E-governance, OLAP ,Data warehousing, Data Mining