This paper includes the application that is implemented at my college. Here is perfect explanation of Data Warehousing and Data Mining with full descr...
The data warehouse allows the storage of data in a format that facilitates its access, but if the tools for deriving information and/or knowledge and presenting them in a format that is useful for ...
Data warehousing and data mining (both data & text) provide a technology that enables the decision-maker in the corporate sector/govt. to process this huge amount of data in a reasonable amo…Description complète
This paper includes the application that is implemented at my college. Here is perfect explanation of Data Warehousing and Data Mining with full description of the project.
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Data Warehousing and Data Mining (1)
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Data Mining is defined as the procedure of extracting information from huge sets of data. Now a day, Data Mining technique placing a vital role in the Information Industry.
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This research paper is about Data Warehousing. It gives you overview about data warehousing and how companies use it. It also tells you about the architecture and working of data warehousing…Full description
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WALCHAND INSTITUTE OF TECHNOLOGY
A PAPER PRESENTATION ON
DATA WAREHOUSING AND DATA MINING AT
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Prof. R. B. Kulkarni (CSE Dept. WIT, Solapur)
INDEX 1. ABSTRACT 2. DATA DATA WARE WAREHO HOUS USIN ING G Introduction Need of Data Warehousing
Purpose of Data Warehousing
Characteristics Life cycle Architecture Tools and technologies Applications
3. DATA MI MINING Introduction Types of Data Mining Major elements of Data Mining
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DATA WAREHOUSING AND DATA MINING ABSTRACT: Fast, Fast, accurat accuratee and scalab scalable le data data analys analysis is techni technique quess are needed needed to extract extract
information from huge pile of data. Data warehouse is a single, integrated source of deci supp suppor ortt info inform rmat atio ion n form formed ed by coll collect ectin ing g data data from from mult multip iple le sour source ces, s, inte intern rnal al
organization as well as external, and transforming and summarizing this information to en
improved decision making. Data warehouse is designed for easy access by users to l
amounts of information, and data access is typically supported by specialized analytical t and applica applicatio tions. ns. Typica Typicall applic applicati ations ons includ includee decisi decision on suppo support rt syste systems ms and exe information system.
Data mining is the exploration and analysis of large quantities of data in orde
discover discover valid, novel, novel, potentially potentially useful, and ultimately ultimately understandable understandable patterns in data.
“An information extraction activity whose goal is to discover hidden facts containe databases”.
The process of extracting valid, previously unknown, comprehensible and action information from large databases and using it to make crucial business decisions.
project entitled “Website Data Mining” is an application of data min Master yourThe semester with Scribd Read Free Foron 30this Days Sign up to vote title which which is built built for for the websit websitee develo developer perss for the their ir effec effectiv tivee creat creation ion of websit web sit & The New York Times Useful Not useful internet. Special offer for students: Only $4.99/month.
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DATA WAREHOUSING Everyd Everyday ay increa increasin singly gly,, organi organizati zations ons are analyz analyzing ing curren currentt and histor historical ical identify useful patterns and support business strategies.
A large amount of the right information is the key to survival in today’s competi
enviro environme nment. nt. And this kind kind of inform informati ation on can be made made availa available ble only only if there’s there’s to integrated enterprise data warehouse. What is data warehousing?
A data warehouse is a subject-oriented, integrated, non-volatile & time-var
collection of data in support of management’s decisions. Need for Data Warehousing:
• IT or business staff spending a lot of time developing special reports for decision-makers
• Lots of PC-based or small server systems obtaining extracts of data incapable of presenti holistic view of the entire gamut of information.
• Same data present on different systems, in different department and users may be unawa this fact. • Difficulty in getting meaningful information in a timely manner.
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• Less analysis by decision makers and policy planners due to non-availability of sophistic
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• Replacement of older, less-responsive decision support systems • Faster time to market for products and services
Data Warehouse Characteristics:
1. Subject-oriented àWH is organized around the major subjects of the enterprise ra
than the major application areas. This is reflected in the need to store decision-sup data rather than application-oriented data.
2. Integrated à because the source data come together from different enterprise-
application applicationss systems. systems. The source source data is often inconsistent inconsistent using..The using..The integrated integrated source must be made consistent to present a unified view of the data to the users.
3. Time-variantàthe source data in the WH is only accurate and valid at some poi
time or over some time interval. The time-variance of the data warehouse is
shown in the extended time that the data is held, the implicit or explicit associatio time with all data, and the fact that the data represents a series of snapshots.
4. Non-volatileàdata is not update in real time but is refresh from OS on a regular b
New data is always added as a supplement to DB, rather than replacement. continually absorbs this new data, incrementally integrating it with previous data
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the massive amount of data stored in an efficient manner. It is a process through which
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1) JUST JUSTIF IFIC ICAT ATIO ION N 2) REQU REQUIR IREM EMEN ENT T ANAL ANALYS YSIS IS 3)
DESIGN
4) DEVELOPMENT & IMPLEMENTATION
5) DEPL DEPLOY OYME MENT NT
DATA WAREHOUSE ARCHITECTURE :
Operational data source1
Meta-data
Operational data source 2
Lightly Manage
High Query summarized data
summarized
Load Manager
data
Operational data source n
Reporting, query,app developme EIS(execut informatio system) to
Detailed data
DBMS
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Operational
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Data m Archive/backup
End-useraccess t
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systems such as the Internet, commercially available DB, or DB assoicated with organization’s suppliers or customers •
Operational datastore(ODS) datastore(ODS)àis a repository of current and integrated operational
used for analysis. It is often structured and supplied with data in the same way as the
warehouse, but may in fact simply act as a staging area for data to be moved into warehouse •
Load manager
also called the frontend component, it performance all the operat
associated associated with the extraction extraction and loading loading of data into the warehouse. warehouse. These opera
include simple transformations of the data to prepare the data for entry into the wareho •
Warehouse managerà performs all the operations associated with the management o
data in the warehouse. The operations performed by this component include analys
data to ensure consistency, transformation and merging of source data, creation of ind
and views, generation of denormalizations and aggregations, and archiving and backin data •
also calle called d back backen end d comp compon onen ent, t, it perfo perform rmss all all the the oper oper Query Quer y manager manageràalso
associ associate ated d with with the manage managemen mentt of user user queries queries.. The operat operation ionss perfor performed med by
component include directing queries to the appropriate tables and scheduling the execu of queries •
End-user access tools àcan be categorized into five main groups: data reporting
query tools, application application development development tools, tools, executive executive informatio information n system system (EIS) t online analytical processing (OLAP) tools, and data mining tools. Master your semester with Scribd Read Free Foron 30this Days Sign up to vote title Tools and Technologies: & The New York Times Useful Not useful Special offer for students: Only $4.99/month.
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The critica criticall steps steps in in the the const construc ructio tion n of a data data wareh warehous ouse: e:
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OLTP systems are the major kinds of enterprise applications: Examples:
Order entry systems, Inventory control systems, Reservation systems, Point-ofsystems, Tracking systems, etc.
•
Executive information system (EIS) :
Present information at the highest level of summarization using corporate busi
measures. They are designed for extreme ease-of-use and, in many cases, only a m is requir required. ed. Graphic Graphicss are usual usually ly genero generousl usly y incorp incorpora orated ted to provid providee at-a indications of performance •
Decision Support Systems (DSS) :
They ideally present information in graphical and tabular form, providing the
with the ability to drill down on selected information. Note the increased detail data manipulation options presented.
DATA MINING What is data mining?
Master your semester with Scribd Read Free Fordifferent 30this Days Sign up to vote on titleperspectives data from Data Mining refers to the process of analyzing the & The New York Times Useful Not useful summarizing it into useful information. Data mining software is one of the numbers of t Special offer for students: Only $4.99/month.
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used used for for analy analyzi zing ng data data from from many many diff differe erent nt dime dimens nsio ions ns or angl angles es categ categor oriz izee
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Different Types of Data Mining: Business, Scientific and Internet Data Mining Five major elements of Data Mining: 1. Extract, transform, & load transaction data on to the data warehouse system. 2. Store and manage data in multidimensional database system. 3. Provide access to business analysts and IT Professionals. 4. Analyze the data by application software. 5. Present the data in useful format such as graph or table.
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DATA MINING: A KDD Process:
Steps of KDD Process: Learni Learning ng the applic applicatio ation n doma domain in Master 1.your semester with Scribd Free Foron 30this Days Sign up to vote title 2. Relevant Relevant prior prior knowledge knowledge and goals of application application Read & The New York Times Useful Not useful 3. Creatin Creating g a target target data data set: set: data data select selection ion Special offer for students: Only $4.99/month.
4. Data Data clean cleaning ing and prepro preproces cessin sing g
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Methods of Data Mining:
1. Classification
2.Regression
3.Clustering 4.Associative rules 5.Visualization
PROJECT ON DATA MINING : “Website “Websi te Data Mining”
We have created an application which works as a data mining for a website develo
The project has been implemented successfully on a local server and has given an exce feedback. •
Aim of the project:
To give a simple graph to a user on the whole information of websites •
Implementation:
The data warehouse that is being used for the project is information gathered survey. The data has been collected to a database. This database is used in the project.
The database contains the information on many websites. This is a huge database. database is formed going to the questionnaires that were subtitled by the users of websites.
application we createdScribd is a web based one. The application creates particular g Master yourThe semester with Read Free Foron 30this Days Sign up to vote title like, pie chart, line chart or bar graph. These graphs are generated as per the param & The New York Times Useful Not useful Cancel anytime.
selected the website builders. The parameters that are selected would look as the fi Special offer for students: Onlyby $4.99/month.
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These constraints entered by the user are considered to generate charts. The abstrac of the data from the database is done in effective manner. The user will just know exam exampl ple, e, a webs websit itee buil builde derr want wantss to know know wher wheree the the socia sociall netw networ orki king ng site sitess ar maximum as per the database will look as below:
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Java Servlet Pages (JSP) is used for the program the application. The database is st
in the Microsoft Access DB. For implementation purpose a local server of Tomcat 6.0 Se is used. For generating the charts in JSP, we made use of the JFreeChart package.
The page navigation is considered for taking the inputs. The traversing is as follow Index.jsp
ganechhart.jsp
In index.jsp, the parameters are taken ta ken from the user. These parameters are posted t
genechart.jsp file in the server. The SQL queries are fixed to generate the appropriate reco
These records are used to build the charts. Example of the code for SQL in JSP is as follo String url="jdbc:odbc:Driver={Microsoft Access Driver(*.mdb)}; DBQ=/FinalDB.mdb;DriverID=22;READONLY=true"; Class.forName("sun.jdbc.odbc.JdbcOdbcDriver"); con=DriverManager.getConnection(url,"",""); st=con.createStatement(); rs = st.executeQuery( sSql ); while( rs.next() ) { out.println( "
" ); for( int i=1; i<=n; i++ ) // Achtung: erste Spalte mit 1 statt 0 out.println( "
" + rs.getString( i ) + "
" ); }
These These records after getting getting formed, formed, an algorithm algorithm is used to get the statistics statistics o data. This algorithm will give the whole implementation of websites that can be use generate the chart. The charts are generated with the following code:
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CONCLUSION
Data Warehousing provides the means to change the raw data into information making making effecti effective ve busine business ss decisi decisions ons-th -thee emphas emphasis is on inform informatio ation, n, not data. data. The warehouse is the hub for decision support data.
Data mining is a useful tool with multiple algorithms that can be tuned for spe
tasks. It can benefit business, medicine, and science. It needs more efficient algorithm speed up data mining process.
REFERENCE
Multidimensional Data analysis and Data Mining
- Arinjay Choudhary, Dr. P.S. Deshande Data Mining and Data Warehousing and OLAP
-A. Berson, S.J. Smith
www.datawarehousingonline.com AND www.Wikipedia.com
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