IT6702 - DATA WAREHOUSING AND DATA MINING

PRESENTEDBY:- V.Balamurugan Assistant professor, CSE Department, Mohamed Sathak Engineering College IT6702 - DATA WAREHOUSING AND DATAMINING 1

Data warehousing is combining data from multiple sources into one comprehensive and easily manipulated database. • The primary aim for data warehousing is to provide businesses with analytics results from data mining, OLAP, Scorecarding and reporting. DATAWAREHOUSING 2

Information is now considered as a key for all the works. • Those who gather, analyze, understand, and act upon information are winners. • Information have no limits, it is very hard to collect information from various sources, so we need an data warehouse from where we can get all the information. NEED FOR DATAWAREHOUSING 3

TODAYS BUISNESSINFORMATION 4

Retrievingdata  Analyzingdata  Extractingdata  DATA WAREHOUSINGINCLUDES:- Loadingdata  Transformingdata  Managingdata  5

Data warehousing is designed to provide an architecture that will make cooperate data accessible and useful to users. • There is no right or wrong architecture. • The worthiness of the architecture can be judge by its use, and concept behind it . • Data Warehouses can be architected in many different ways, depending on the specific needs of a business. DATA WAREHOUSEARCHITECTURE 6

Typical Data WarehousingEnvironment 7

An operational data store (ODS) is basically a database that is used for being an temporary storage area for a datawarehouse. • Its primary purpose is for handling data which are progressively in use. • Operational data store contains data which are constantly updated through the course of the business operations. 8

ETL (Extract, Transform, Load) is used to copy data from:- • ODS to data warehouse staging area. • Data warehouse staging area to data warehouse . • Data warehouse to data mart . • ETL extracts data, transforms values of inconsistent data, cleanses "bad" data, filters data and loads data into a target database. 9

The Data Warehouse Staging Area is temporary location where data from source systems is copied. • It increases the speed of data warehouse architecture. • It is very essential since data is increasing day by day.

The purpose of the Data Warehouse is to integrate corporate data. • The amount of data in the Data Warehouse is massive. Data is stored at a very deep level of detail. • This allows data to be grouped in unimaginable ways. • Data Warehouses does not contain all the data in the organization ,It's purpose is to provide base that are needed by the organization for strategic and tactical decision making.

ETL extract data from the Data Warehouse and send to one or more Data Marts for use of users. • Data marts are represented as shortcut to a data warehouse ,to save time. • It is just an partition of data present in data warehouse. • Each Data Mart can contain different combinations of tables, columns and rows from the Enterprise Data Warehouse.

Easy access to frequently needed data. • Creates collective view by a group of users. • Improves user response time. • Ease of creation. • Lower cost than implementing a full Data warehouse REASONS FOR CREATING AN DATAMART

The non-trivial extraction of implicit, previously unknown, and potentially useful information from large databases. • Extremely large datasets • Useful knowledge that can improve processes • – Cannot be done manually DATAMINING

Where Has it Come From? 15 10/13/08 03:57AM

Databases today are huge: • More than 1,000,000 entities/records/rows • From 10 to 10,000 fields/attributes/variables • Giga-bytes and tera-bytes • Databases a growing at an unprecendented rate The corporate world is a cut-throat world • Decisions must be made rapidly • Decisions must be made with maximum knowledge  Motivation  

Extract, transform, and load transaction data onto the data warehouse system. Store and manage the data in a multidimensional database system. Provide data access to business analysts and information technology professionals. Analyze the data by application software. Present the data in a useful format, such as a graph or table   How does data miningwork?   

Accuracy • Clarity • DirtyData • Scalability • Speed • Validation DATA MININGMEASURES

Typical Applications of DataMining 10/13/08 03:57AM

      Engineering and Technology Medical Science Business Combating Terrorism Games Research and Development ADVANTAGES OF DATAMINING

In Electrical Power Engineering • used for condition monitoring of high voltage electrical equipment • vibration monitoring and analysis of transformer on-load tap-changers • Education • to concentrate their knowledge Engineering andTechnology

Data mining has been widely used in area of bioinformatics , genetics • DNA sequences and variability in disease susceptibility which is very important to help improve the diagnosis, prevention and treatment of the diseases MedicalScience

In Customer Relationship Management applications • It Translate data from customer to merchant Accurately • Distribute Business Processes • Powerful Tool For Marketing BUSINESS

Concept used by Interpol against terrorists for searching their records by Multistate Anti- Terrorism Information Exchange • In the Secure Flight program , Computer Assisted Passenger Pre screening System , Semantic Enhancement Combatingterrorism

for certain combinatorial games, also called table bases (e.g. for 3x3-chess) • It includes extraction of human-usable strategies • Berlekamp in dots-and-boxes and Joh Nunn in chess endgames are notable examples Games

Helps to Develop the search algorithms • It offers huge libraries of graphing and visualisation softwares • The users can easily create the models optimally Research AndDevelopment

         Angoss Software Infor CRM Epiphany Portrait Software SAS G-Stat SPSS ThinkAnalytics Unica Viscovery List of the top eight data-mining software vendors in 2008

THANK YOU

IT6702 - DATA WAREHOUSING AND DATA MINING