Clase2 introdw

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Introduccion a BI y conceptos

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Clase2 introdw

  1. 1.  Data sources often store only current data, not historical data Corporate decision making requires a unified view of all organizational data, including historical data 2
  2. 2.  Data warehouse A physical repository where relational data are specially organized to provide enterprise-wide, cleansed data in a standardized format A DW delivers a collection of integrated data used to support the decision making process for the enterprise 3
  3. 3.  A data warehouse is a repository (archive) of information gathered from multiple sources, stored under a unified schema, at a single site  Greatly simplifies querying, permits study of historical trends  Shifts decision support query load away from transaction processing systems 4
  4. 4. 5
  5. 5.  Characteristics of data warehousing  Subject oriented ▪ organized based on use: sales, products, customers 6
  6. 6.  Characteristics of data warehousing  Integrated ▪ inconsistencies removed 7
  7. 7.  Characteristics of data warehousing  Time variant: data are normally time series, A warehouse maintains historical data  Nonvolatile: stored in read-only format, periodically refreshed, Changes are recorded as new data 8
  8. 8.  Characteristics of data warehousing  Summarized ▪ in decision-usable format  Large volume ▪ data sets are quite large  Non normalized ▪ often redundant  Metadata ▪ data about data are stored 9
  9. 9.  Integrated, company-wide view of high-quality information (from disparate databases) Separation of operational and informational systems and data (for improved performance) 10
  10. 10.  Data mart A departmental data warehouse that stores only relevant data  Focuses on a particular subject or department 11
  11. 11. Legacy systems Legacyfeed data to Systems Sales the Finance Data Mart Data Mart Operational Marketing Data Store Data Martwarehouse. Accountin Operational g Data Store Data Mart The warehouse Operational Organizational feeds Data Store Data Warehouse specialized Operationalinformation to Data Storedepartments. 12
  12. 12. Organizational Data Warehouse The data Corporate Highly granular data Normalized design Finance Data Mart Sales Data Mart Marketing Robust historical data mart serves Large data volume Data Model driven data Versatile Data Martthe needs of General purpose DBMS technologies Accting Data Mart one business Data Marts Departmentalizedunit, not the Summarized, aggregated data Star join designorganization. Limited historical data Limited data volume Requirements driven data Organizational Focused on departmental Data needs Multi-dimensional DBMS Warehouse technologies 13
  13. 13.  Dependent data mart A subset that is created directly from a data warehouse  Quality data  Support enterprise wide data model 14
  14. 14.  Independent data mart A small data warehouse designed for a strategic business unit or a department, but its source is not an EDW 15
  15. 15.  Operational data stores (ODS) A type of database often used as an interim area for a data warehouse, especially for customer information files Volatile Used for short-term decisions involving mission-critical application  Store only very recent information 16
  16. 16.  Oper marts An operational data mart. An oper mart is a small-scale data mart typically used by a single department or functional area in an organization  The data for an oper-mart come from an ODS 17
  17. 17.  Enterprise data warehouse (EDW)  Is a large scale DW that is used across the enterprise for decision support  A technology that provides a vehicle for pushing data from source systems into a data warehouse 18
  18. 18. 19
  19. 19.  Metadata Data about data. In a data warehouse, metadata describe the contents of a data warehouse and the manner of its use 20
  20. 20.  Metadata  As with other databases, a warehouse must include a metadata repository ▪ Information about physical and logical organization of data ▪ Information about the source of each data item and the dates on which it was loaded and refreshed 21
  21. 21.  Direct benefits of a data warehouse  Allows end users to perform extensive analysis  Allows a consolidated view of corporate data  Better and more timely information  Enhanced system performance  Simplification of data access  Data integration  No more redundancy  Consistency of data content 22
  22. 22.  Direct benefits of a data warehouse  Improved data quality  Historical enterprise data  Unlimited, ad-hoc reporting  Reliable trend analysis reporting  Faster data delivery and data access  Business intelligence (BI) capabilities 23
  23. 23.  Indirect benefits result from end users using these direct benefits  Enhance business knowledge  Present competitive advantage  Enhance customer service and satisfaction  Facilitate decision making  Help in reforming business processes 24
  24. 24.  DECISION SUPPORT SYSTEMS AND BUSINESS INTELLIGENCE. Turban Modern Data Warehousing, Mining, and Visualization: Core Concepts. George M. Marakas Modern Database Management.9th Edition.Jeffrey A. Hoffer, Mary B. Prescott, Heikki Topi 25

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