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Managing Information Resources

Managing Information Resources. Managing Data. 1. Managing Information. 2. Managing Contents. 3. Concepts & Definitions. Data Facts devoid of meaning or intent e.g. structured data in DB Information Data that has meaning (data in context)

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Managing Information Resources

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  1. Managing Information Resources

  2. Managing Data 1 Managing Information 2 Managing Contents 3

  3. Concepts & Definitions • Data • Facts devoid of meaning or intent • e.g. structured data in DB • Information • Data that has meaning (data in context) • e.g. course selection info in a student management system, documents, voice, video... • Knowledge: information with direction or intent • Content • Term for the Web age • e.g. text, graphics, animation, maps, photos, film clips etc.

  4. Information Resource Management Responsibilities • Corporate databases • Distributed • Various data models • Data warehouse • Information • Documents • Web contents • Knowledge management • Explicit knowledge (know-what) • Tacit knowledge (know-how) • IS has been continually managing new forms of information resources

  5. Managing Data • DBMS • The three-level database model • Level 1: the conceptual level • Containing the various "user views" of the corporate data that each application program uses • Level 2: the logical level • Logical views of an organizations data as under the control of the DBAs • Level 3: the physical level • Specifying the way the data is physically stored • Level 2 absorbs changes made at level 3

  6. Level 1 Table Student Level 2 Table CourseSelect Table Course Level 3

  7. Four Data Models • Hierarchical mode • structures data so that each element is subordinate to another in a strict hierarchical manner (Parent & child) • Network model • Allows each data item to have more than one parent, • Relationships stated by pointers stored with the data • Relational model • Object model • Storing and managing data as objects • A competitive candidate for storing XML data

  8. XML • XML (eXtensible Markup Language) is a self-describing markup language for applying structure to data • Not limited to predefined tags • Human readable • Machine readable • Portability • Java: portable programs • XML: portable data

  9. XML---Semi-Structured Data Unstructured data: TEXT More Structure XML Structured data: Less Structure Structured (relational) Data

  10. XML Data Model & Native Storage • Native XML Database • Defines a (logical) model for an XML document and stores and retrieves documents according to that model. • Has an XML document as its fundamental unit of (logical) storage imdb show review review title @year “Fugitive, The” “1993” suntimes nyt … … rating reviewer “two...” “gives” “Roger Ebert”

  11. Getting Corporate Data into Shape (1) • The Problem: Management can not get consistent view across the enterprise • 1960s-1970: application developed in separation  "information islands" • Different units in an organization developed their used their own database and their own applications • Inconsistent data definitions • Duplicate data

  12. Getting Corporate Data into Shape (2) • The Cause: an application-driven approach • Getting applications running as quickly as possible • The Solution: a data-driven approach • Data of interest  data source  applications • Usually evolves from the application-driven chaos

  13. Getting Corporate Data into Shape (3) • Managing data as a corporate resource is more than installing a DBMS • DBA: administering databases and software that manages them • Data administrator: managing enterprise-wide data resources • Clean up the data definitions • Control shared data • Manage data distribution, and • Maintain data quality

  14. Getting Corporate Data into Shape (4) • ERPs aim to integrate all data and processes of an organization into a unified system • Automate and integrate the majority of business processes • Share common data and practices across the entire enterprise • Produce, access and manage information in a real-time environment • Configure application to meet business needs • Key: a unified database • Provide management a corporate-wide view of operations

  15. Managing Data 1 Managing Information 2 Managing Contents 3

  16. Four Types of Information (1) • Two structures of information • Record-based: facts about entities • Document-based: dealing with concepts • Housed in documents, messages, video, audio clips...

  17. Four Types of Information (2) • Two sources of information: internal and external • Internal record-based information: traditional focus of IS • External record-based information: public DB • Internal and external document-based information have received little attention from IS until recently • However, it is estimated that 90% of an organization's information is in documents rather than structured databases (Sprague, 1995).

  18. Technologies for Managing Information • The two different structures of information are managed in different ways • Record-based • Data warehouse • Document-based • Document management systems • Web content management

  19. What is Data Warehouse? • “A data warehouse is a subject-oriented, integrated, time-variant, and nonvolatile collection of data in support of management’s decision-making process.”—W. H. Inmon

  20. Data Warehouse—Subject-Oriented • Organized around major subjects, such as customer, product, sales • Focusing on the modeling and analysis of data for decision makers, not on daily operations or transaction processing • Provide a simple and concise view around particular subject issues by excluding data that are not useful in the decision support process

  21. Data Warehouse—Integrated • Constructed by integrating multiple, heterogeneous data sources • Relational databases, flat files, on-line transaction records • Data cleaning and data integration techniques are applied. • Naming conventions, encoding structures, attribute measures, etc. among different data sources • When data is moved to the warehouse, it is converted.

  22. Data Warehouse—Time Variant • The time horizon for the data warehouse is significantly longer than that of operational systems • Operational database: current value data • Data warehouse data: provide information from a historical perspective (e.g., past 5-10 years) • Every key structure in the data warehouse • Contains an element of time, explicitly or implicitly

  23. Data Warehouse—Nonvolatile • A physically separate store of data transformed from the operational environment • Operational update of data does not occur in the data warehouse environment • Does not require transaction processing, recovery, and concurrency control mechanisms • Requires only two operations in data accessing: • Initial loading of data and access of data

  24. Data Warehouse vs. Heterogeneous DBMS • Traditional heterogeneous DB integration: A query driven approach • Build wrappers/mediators on top of heterogeneous databases • When a query is posed to a client site, a meta-dictionary is used to translate the query into queries appropriate for individual heterogeneous sites involved, and the results are integrated into a global answer set • Complex information filtering, compete for resources • Data warehouse: update-driven, high performance • Information from heterogeneous sources is integrated in advance and stored in warehouses for direct query and analysis

  25. Data Warehouse vs. Operational DBMS • OLTP (on-line transaction processing) • Major task of traditional relational DBMS • Day-to-day operations: purchasing, inventory, banking, manufacturing, payroll, registration, accounting, etc. • OLAP (on-line analytical processing) • Major task of data warehouse system • Data analysis and decision making

  26. OLTP vs. OLAP

  27. Typical OLAP Operations • Roll up (drill-up): summarize data • By climbing up hierarchy or by dimension reduction • Drill down (roll down): reverse of roll-up • From higher level summary to lower level summary or detailed data, or introducing new dimensions • Slice and dice: project and select • Pivot (rotate): • Reorient the cube, visualization, 3D to series of 2D planes

  28. Other sources Extract Transform Load Refresh Operational DBs Data Warehouse: A Multi-Tiered Architecture Monitor & Integrator OLAP Server Metadata Analysis Query Reports Data mining Serve Data Warehouse Data Marts Data Sources Data Storage OLAP Engine Front-End Tools

  29. Document Management • Estimated that 90% of an organization’s information is in documents rather than structured databases • Types of Documents • Contracts and Agreements • Reports • Manuals and Handbooks • Correspondence • Memos • Drawings and Blueprints • …

  30. Fundamental Roles of Documents • 4 Fundamental roles of documents • As a product, or support for a product • As a fundamental mechanism for communication among people and groups within an organization and between organizations. • As the primary vehicle for business processes • As an important part of organizational memory

  31. Electronic Document • An electronic document has the following characteristics • holds information of multiple media: text, graphics, audio, video • contains multiple structures: headers, footers, TOC, sections, paragraphs, tables • dynamic: can be updated on the fly • may depend on other documents

  32. Limitations of RDBMS • Limitations of RDBMS for document management • Based on E-R data models • Suitable for structured data • Traditional business applications, decision support systems, reporting tools • No inherent support to manage electronic documents

  33. Electronic Document Management System (1) • An EDMS is a computer system used to track and store electronic documents and/or images of paper documents. • Allows users to create a document or capture a hard copy in electronic form • Commonly provided capabilities • Storage • Versioning • Metadata • Security • Indexing • Retrieval

  34. Electronic Document Management System (2) Records created & received electronically Records created & received in hard copy Records are filed & managed for access & maintenance electronically

  35. Electronic Document Management System (3) • An EDMS usually provides a single view of multiple databases • An EDMS may include: • Scanners and Optical Character Recognition (OCR) for document capture • Printers for creating hard copies • Storage devices such as redundant array of independent disks systems and computer server • Server programs for managing the databases that contain the documents.

  36. Managing Data 1 Managing Information 2 Managing Contents 3

  37. Content Management (1) • Content is a core management discipline underlying online business • Without production-level Web content, management processes, and technologies, large-scale e-business is not possible • The adoption of the XML • The language for manipulating the content to work with transaction applications

  38. Content Management (2) • Traditional “home-grown“ content management • The Webmaster was the publishing bottle neck • 3 phases of content management life cycle • Input-process-output

  39. Content Management (3) • Content creation and acquisition • Focus on creating content quality • Distribute content creation and maintenance to business departments with centralized coordination and control • Content administration and safeguarding • Emphasis on efficiency • Use tools for content administration and work flow control

  40. Content Management (4) • Content deployment and presentation • Emphasis on effectiveness • i.e. Presenting the content so that it attracts visitors, allows them to navigate the site easily, and leads them to the desired actions • Features to attract and keep visitors • Personalization: allowing visitors to customize how they view the page • Localization: tailoring a site to a culture, market or locale • Multichannel distribution: appropriate display for various devices

  41. Content Management Systems (1) • A Content Management System (CMS) is software that makes it easier to create, edit and publish content on a web site. • Back-end to help create, edit and manage content • Front-end to deliver content dynamically to various endpoints • Work flow control in moving and adding contents

  42. Content Management Systems (2) Content Delivery “Front-end" functions for delivering and displaying content Content Delivery Application Assembled, tagged & formatted assets Workflow “Back-end” functions for creating, editing, producing, and administering a site and its content Content Management Application Content Repositories Individual Contributors • Databases • DB Schemas • XML, HTML • Web Services • Portals • Web apps • PeopleSoft • MBM • Docs, ppts • Brochures • Photos • Logos • Contracts • Syllabus • Schedule • C:\ Structured Content Unstructured Content

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