DATA WAREHOUSING AND DATA MINING

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Basics of Data Warehousing and Data Mining

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DATA WAREHOUSING AND DATA MINING

  1. 1. DATA WAREHOUSING AND DATA MINING PRESENTED BY :- ANIL SHARMA B-TECH(IT)MBA-A REG NO : 3470070100 PANKAJ JARIAL BTECH(IT)MBA-A REG NO : 3470070086
  2. 2. DATA WAREHOUSING <ul><li>Data warehousing is combining data from multiple sources into one comprehensive and easily manipulated database. </li></ul><ul><li>The primary aim for data warehousing is to provide businesses with analytics results from data mining, OLAP, Scorecarding and reporting. </li></ul>
  3. 3. NEED FOR DATA WAREHOUSING <ul><li>Information is now considered as a key for all the works. </li></ul><ul><li>Those who gather, analyze, understand, and act upon information are winners. </li></ul><ul><li>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. </li></ul>
  4. 4. TODAYS BUISNESS INFORMATION
  5. 5. <ul><li>Retrieving data </li></ul><ul><li>Analyzing data </li></ul><ul><li>Extracting data </li></ul><ul><li>Loading data </li></ul><ul><li>Transforming data </li></ul><ul><li>Managing data </li></ul>DATA WAREHOUSING INCLUDES:-
  6. 6. DATA WAREHOUSE ARCHITECTURE <ul><li>Data warehousing is designed to provide an architecture that will make cooperate data accessible and useful to users. </li></ul><ul><li>There is no right or wrong architecture. </li></ul><ul><li>The worthiness of the architecture can be judge by its use, and concept behind it . </li></ul><ul><li>Data Warehouses can be architected in many different ways, depending on the specific needs of a business.  </li></ul>
  7. 7. Typical Data Warehousing Environment
  8. 8. <ul><li>An operational data store (ODS) is basically a database that is used for being an temporary storage area for a datawarehouse. </li></ul><ul><li>Its primary purpose is for handling data which are progressively in use. </li></ul><ul><li>Operational data store contains data which are constantly updated through the course of the business operations. </li></ul>
  9. 9. <ul><li>ETL (Extract, Transform, Load) is used to copy data from:- </li></ul><ul><li>ODS to data warehouse staging area. </li></ul><ul><li>Data warehouse staging area to data warehouse . </li></ul><ul><li>Data warehouse to data mart . </li></ul><ul><li>ETL extracts data, transforms values of inconsistent data, cleanses &quot;bad&quot; data, filters data and loads data into a target database.   </li></ul>
  10. 10. <ul><li>The Data Warehouse Staging Area is temporary location where data from source systems is copied.  </li></ul><ul><li>It increases the speed of data warehouse architecture. </li></ul><ul><li>It is very essential since data is increasing day by day. </li></ul>
  11. 11. <ul><li>The purpose of the Data Warehouse is to integrate corporate data. </li></ul><ul><li>The amount of data in the Data Warehouse is massive.  Data is stored at a very deep level of detail. </li></ul><ul><li>This allows data to be grouped in unimaginable ways. </li></ul><ul><li>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.   </li></ul>
  12. 12. <ul><li>ETL extract data from the Data Warehouse and send to one or more Data Marts for use of users. </li></ul><ul><li>Data marts are represented as shortcut to a data warehouse ,to save time. </li></ul><ul><li>It is just an partition of data present in data warehouse. </li></ul><ul><li>Each Data Mart can contain different combinations of tables, columns and rows from the Enterprise Data Warehouse.  </li></ul>
  13. 13. REASONS FOR CREATING AN DATA MART <ul><li>Easy access to frequently needed data. </li></ul><ul><li>Creates collective view by a group of users. </li></ul><ul><li>Improves user response time. </li></ul><ul><li>Ease of creation. </li></ul><ul><li>Lower cost than implementing a full Data warehouse </li></ul>
  14. 14. DATA MINING <ul><li>The non-trivial extraction of implicit, previously unknown, and potentially useful information from large databases. </li></ul><ul><li>– Extremely large datasets </li></ul><ul><li>– Useful knowledge that can improve </li></ul><ul><li>processes </li></ul><ul><li>– Cannot be done manually </li></ul>
  15. 15. Where Has it Come From ?
  16. 16. Motivation <ul><li>Databases today are huge: </li></ul><ul><li>– More than 1,000,000 entities/records/rows </li></ul><ul><li>– From 10 to 10,000 fields/attributes/variables </li></ul><ul><li>– Giga-bytes and tera-bytes </li></ul><ul><li>Databases a growing at an unprecendented rate </li></ul><ul><li>The corporate world is a cut-throat world </li></ul><ul><li>– Decisions must be made rapidly </li></ul><ul><li>– Decisions must be made with maximum knowledge </li></ul>
  17. 17. How does data mining work? <ul><li>Extract, transform, and load transaction data onto the data warehouse system. </li></ul><ul><li>Store and manage the data in a multidimensional database system. </li></ul><ul><li>Provide data access to business analysts and information technology professionals. </li></ul><ul><li>Analyze the data by application software. </li></ul><ul><li>Present the data in a useful format, such as a graph or table </li></ul>
  18. 18. DATA MINING MEASURES <ul><li>Accuracy </li></ul><ul><li>Clarity </li></ul><ul><li>Dirty Data </li></ul><ul><li>Scalability </li></ul><ul><li>Speed </li></ul><ul><li>Validation </li></ul>
  19. 19. Typical Applications of Data Mining
  20. 20. ADVANTAGES OF DATA MINING <ul><li>Engineering and Technology </li></ul><ul><li>Medical Science </li></ul><ul><li>Business </li></ul><ul><li>Combating Terrorism </li></ul><ul><li>Games </li></ul><ul><li>Research and Development </li></ul>
  21. 21. Engineering and Technology <ul><li>In Electrical Power Engineering </li></ul><ul><li>- used for condition monitoring of high </li></ul><ul><li>voltage electrical equipment </li></ul><ul><li>- vibration monitoring and analysis of </li></ul><ul><li>transformer on-load tap-changers </li></ul><ul><li>Education </li></ul><ul><li>- to concentrate their knowledge </li></ul>
  22. 22. Medical Science <ul><li>Data mining has been widely used in area of bioinformatics , genetics </li></ul><ul><li>DNA sequences and variability in disease susceptibility which is very important to help improve the diagnosis, prevention and treatment of the diseases </li></ul>
  23. 23. BUSINESS <ul><li>In Customer Relationship Management applications </li></ul><ul><li>It Translate data from customer to merchant Accurately </li></ul><ul><li>Distribute Business Processes </li></ul><ul><li>Powerful Tool For Marketing </li></ul>
  24. 24. Combating terrorism <ul><li>Concept used by Interpol against terrorists for searching their records by Multistate Anti-Terrorism Information Exchange </li></ul><ul><li>In the Secure Flight program , Computer Assisted Passenger Pre screening System , Semantic Enhancement </li></ul>
  25. 25. Games <ul><li>for certain combinatorial games, also called table bases (e.g. for 3x3-chess) </li></ul><ul><li>It includes extraction of human-usable strategies </li></ul><ul><li>Berlekamp in dots-and-boxes and Joh Nunn in chess endgames are notable examples </li></ul>
  26. 26. Research And Development <ul><li>Helps to Develop the search algorithms </li></ul><ul><li>It offers huge libraries of graphing and visualisation softwares </li></ul><ul><li>The users can easily create the models optimally </li></ul>
  27. 27. List of the top eight data-mining software vendors in 2008 <ul><li>Angoss Software </li></ul><ul><li>Infor CRM Epiphany </li></ul><ul><li>Portrait Software </li></ul><ul><li>SAS </li></ul><ul><li>G-Stat </li></ul><ul><li>SPSS </li></ul><ul><li>ThinkAnalytics </li></ul><ul><li>Unica </li></ul><ul><li>Viscovery </li></ul>
  28. 28. <ul><li>THANK YOU </li></ul>

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