MIS619 Report On data mining virtual university mis619 projects
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PROJECT ON DATA MINING AND DATA WAREHOUSING
Introduction :
What is Data Warehousing? Simply defined, a Data Warehousing is a collection of data designed to support managements decision making Data warehousing contain a wide variety of data that present a coherent picture of business conditions at a single point in time Typically a Data Warehousing is housed on enterprise mainframe server. It is a central repository for all or a significant part of all data that on enterprise’s numerous business systems collects. . The wasn’t always the case.
Data warehousing as quickly evolved into a unique and popular business already consider their system to be key components of their It strategy and architecture deployed for businesses of all sizes and all types. Hardware vendors have quickly developed modules and services that specifically target the data warehousing market. This paper will introduce key concepts surrounding the data warehousing system.
NATIONAL COMPUTER COLLEGE
GUIDED BY : CREATED BY :
Mrs. Chandani Dave Miss Ashwini Harke
Mrs. Ragini Sharma Miss Preetiba Jadeja
Miss Sahin Alware
INTRODUCTION :
· DATA MINING
· DATA WAREHOUSING
ABOUT
· Design issues for Data Warehousing
· Analysis process of Data warehousing
- Standard reports and Quarries
- Tool to be used against the Data Warehousing
- Practical Best Practices for Data Warehousing
· Data Conversion Process
· Process of Data Warehouse
· Application of Data Warehouse
DATA MINING
By this point in time, you've probably heard a good deal about data mining -- the database industry's latest buzzword. What's this trend all about? To use a simple analogy, it's finding the proverbial needle in the haystack. In this case, the needle is that single piece of intelligence your business needs and the haystack is the large data warehouse you've built up over a long period of time.
Through the use of automated statistical analysis (or "data mining") techniques, businesses are discovering new trends and patterns of behavior that previously went unnoticed. Once they've uncovered this vital intelligence, it can be used in a predictive manner for a variety of applications.
DATA WAREHOUSING
Executives today expect, and often receive, the good, timely information they need. To make inform decisions and lead their companies into the next decade. The wasn’t always the case.
Data warehousing as quickly evolved into a unique and popular business already consider their system to be key components of their It strategy and architecture deployed for businesses of all sizes and all types. Hardware vendors have quickly developed modules and services that specifically target the data warehousing market. This paper will introduce key concepts surrounding the data warehousing system.
What is Data Warehousing? Simply defined, a Data Warehousing is a collection of data designed to support managements decision making Data warehousing contain a wide variety of data that present a coherent picture of business conditions at a single point in time Typically a Data Warehousing is housed on enterprise mainframe server. It is a central repository for all or a significant part of all data that on enterprise’s numerous business systems collects.
Design issues for Data Warehousing
Discussion of building a Data Warehousing a Data Warehousing is a repository (or archive) of INFO gathered from multiple sources stored, under a unified scheme, at a single site. Once gathered, data are stored for a long time permitting excess to historical data.
Analysis process of Data warehousing
Analysis process of data ware houses range from the most basic (Query & Reporting to the more complex (Statically analysis) to the most complex (Data mining)
ç Standard reports and Quarries
Many users of the Data Ware Houses need to access set of the standard reports and quarries. It is desirable to periodically automatically produce a setup standard reports that are required by many different users. When these users need a particular report, they can just view the report that has already been run by the Data Warehousing system rather then running bye particularly useful for reports that take a long time to run. Such a facility would require report server software.
ç Tool to be used against the Data Warehousing
One of the objectives of the data warehousing is to make it as flexible and as open as possible. It is not desirable to set a steep entry price in terms of software and training for using the Data warehouse. The Data Warehouse should be accessible by as many end-users tools and platforms as possible. Yet it is not possible to make every feature of the Data Warehouse available from every end user too.
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DATA CONVERSION PROCESS
The data conversion process for a data warehousing is complex, time consuming and unglamorous. It is also the very root of a good functional “data” is the operational operative word in “Data Warehouse” Quality data conversion are important to the Data Warehouse because the warehouse holds the information that is by to a corporation decision making process. For a corporation to obtained the ultimate goals and promises of data warehouse, It must understand that how critical the data conversion process is. Who involved before beginning the conversion process the Data Warehousing team completes the design and physical data model for the data warehouse and generates the toyed schemes.
Process of Data Warehouse
Data warehousing describes the process of defining populating and using a data warehouse. Data Warehouses emphasis the capture of data from diverse sources for useful analysis and access. Data from various transaction processing application and other sources is selectively extracted and organized on the data warehouse Database for use by analytical applications and user quarries.
ç Practical Best Practices for Data Warehousing
Data Warehousing is an on going process not something that it built once and left to run. Some best practices for Data Warehousing consist of the following.
Build organizational commitment while managing user expectation.
A dynamic model should consider the following-
- Business Goals / Objectives.
- Business Areas / Functions.
- Improvement opportunity.
- Knowledge / Information.
- Data
- Structured agenda frames
- Improved participants.
- Trained objective 3rd party facilitations.
- Make smart technology investments that are driven by business needs Businesses face concerns with
- Data Source Challenges
- End User Requirement
- Deployment Maintenance Issues
Application of Data Warehouse
Some of the activity against today data warehousing is pre determined and not much different from traditional analysis activity. Other process such as multi dimension analysis and visualization where not available with traditional analysis tools and method. Some of the users of Data Warehouses are as under.
- Data Warehouses are based for customer relationship. Management System because they can be used for consolidator customers data and identifying areas customer satisfaction and frustration.
- Warehouse are also used for dictation, product repositioning analysis profit center discovery and cooperate assets management for retailers can help identify customers demographic characteristic identify shopping patterns direct mailing responses.
Read more at http://vustudents.ning.com/group/mis619finalprojectmanagementinformationsystem/forum/topics/project-report-on-data-warehousing-and-data-minning#xPd8VjmSsS5pBxPG.99
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