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Managing Data: DBMS and Data Warehousing

Explore the difficulties in managing data and learn about the solutions provided by DBMS and data warehousing. Understand the advantages of DBMS, the data life cycle process, and the hierarchy of data. Discover the benefits of the database approach and data modeling. Learn about data warehousing, datamarts, and web-based data management systems.

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Managing Data: DBMS and Data Warehousing

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  1. Chapter 3 Information Technology For Management 6th Edition Turban, Leidner, McLean, Wetherbe Lecture Slides by L. Beaubien, Providence College John Wiley & Sons, Inc. Data Management: Data, Databases and Warehousing Chapter 3

  2. Data Management • Difficulties with managing data • Solutions tomanaging data • Describe DBMS • Describe Data Warehousing and Analytical Processing Chapter 3

  3. The Traditional Approach To Data Management Chapter 3

  4. Databases • A database is an organized logical grouping of related files. • Centralized databases - all the related files are located in one physical location • Distributed database • Replicated database • Partitioned database • Considerations • Failure • Access speed • Maintaining consistency • Security Chapter 3

  5. The Database Approach to Data Management- Database Management Systems (DBMS) Chapter 3

  6. Advantages of DBMS • Query ability (two types) • Concurrency • Backup and replication • Rule enforcement • Security • Computation Chapter 3

  7. DBMS (cont’d) • DBMS provides the ability for many users to share and process data by providing twoviews of the database • Physical view • Logical view • DBMS Languages • DDL • DML Chapter 3

  8. Data Life Cycle Process Chapter 3

  9. Transactional vs. Analytical Data Processing • Transactionalprocessing takes place in operational systems (TPS) that provide the organization with the capability to perform business transactions and produce transaction reports. The data are organized mainly in a hierarchical structure and are centrally processed. This is done primarily for fast and efficient processing of routine, repetitive data. • Supplementary activity to transaction processing is calledanalytical processing, which involves the analysis of accumulated data. Analytical processing, sometimes referred to as business intelligence, includes data mining, decision support systems (DSS), querying, and other analysis activities. These analyses place strategic information in the hands of decision makers to enhance productivity and make better decisions, leading to greater competitive advantage. Chapter 3

  10. Forms for Modeling Data (ERD) • Business Processes • Entities (for which data is collected) • Attributes (characteristics of an entity) • Relations Chapter 3

  11. Relational Models Describe data using a standard tabular format with all data elements placed in two-dimensional tables.

  12. Hierarchy of Data Chapter 3

  13. The Hierarchy of Data Chapter 3

  14. Advantages of the Database Approach Chapter 3

  15. Data ModelingKey Considerations • Content – What data should be collected, and at what cost? • Access – What data should be provided to which users and when? • Logical structure – How should data be arranged so it makes sense to a given user? • Physical organization – Where should data be physically located? Chapter 3

  16. Data Warehouse • DW is a repository of data that are organized to be readily acceptable for analytical processing activities (DSS, querying, data mining) • Organization • Standardization of data • Relational • Delivery of DWH content to users on the intranet and extranet (online banking) • Not all data are necessarily transferred to data warehouse • Three tier vs two tier architecture Chapter 3

  17. The Data Warehouse & Data Management Chapter 3

  18. Web-based Data Management Systems – content and information Chapter 3

  19. Data warehousing is most appropriate when • Large amounts of data to be accessed • The operational data is stored i different systems • Large number of users (AT&T) • Extensive end-user computing Chapter 3

  20. Datamarts • The high cost o DWH confines their use to large companies • A datamart is a small warehouse designed for a department • Two types • Dependent • Standalone Chapter 3

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