1. Evolution of Information Technology Infrastructure

2. Definitions  Information Technology (IT) Infrastructure: physical facilities, services and management that support computing resources Information Technology Hardware/Systems Software Database Telecommunications & Networks IT personnel

3. Definitions  Information Systems (IS) Architecture: the “plan” that aligns IT infrastructure with business needs Help people effectively fulfill their information needs What is the focus of the IT applications?

4. Adapted from "Intranets and Middleware", HBR 397-118.

5. PC/LAN Client/Server db Distributed db Web Services Mainframe Evolution of Information Technology Infrastructure

6. Data Processing Era  IT Infrastructure (host-centric processing) Hardware: Mainframe with text-based terminals Systems Software: Batch systems Data Storage: independent “files” for each functional application Telecommunications: Limited support of distributed operations IT Personnel: technically oriented Mainframe

7. IS Architecture: Transaction Processing System (TPS)  Emerged in the early days of IS Collect, store, and process transactions Source documents are basis for input Perform routine, repetitive tasks Independent functional applications Found in all functions of an organization If they fail, the whole organization may suffer  Efficiency Focus Automate “highly structured” decision processes Mainframe

8. IS Architecture: Management Information System (MIS)  Convert/use TPS data to support monitoring Alert managers to problems or opportunities Provide periodic and routine reports e.g., summary reports, exception reports, comparison reports Starting toward an effectiveness focus Provide structured information to support decision making Resulted in “Information overload” Mainframe

9. IS Architecture: Centralized Corporate Structure Executive Operational Managerial Inbound Logistics Purchasing Raw Materials ProductionFinished Goods Outbound Logistics Sales Functional Transaction Processing System Management Information System Mainframe

10. Micro-Computing Era  IT Infrastructure (PC environment) Hardware: PCs (low cost compared to mainframe) Systems Software: DOS Data storage: Individual files linked to apps Telecommunications: low-speed LANs IT Personnel: technically oriented & mainframe biased PC/LAN

11. IS Architecture: Desktop Support Systems  Proliferation of desktop applications Why? TPS/MIS were not providing information needed to support decisions Needed an effectiveness focus “End-user” development Undocumented spreadsheet models Proliferation of localized data storage PC/LAN db

12. IS Architecture Executive Operational Managerial Inbound Logistics Purchasing Raw Materials ProductionFinished Goods Outbound Logistics Sales Functional Transaction Processing System Management Information System Desktop Decision Support System PC/LAN

13. Client/Server Era  IT Infrastructure (distributed computing environment) Hardware: PCs and Specialized Servers Systems Software: Network Operating Systems, 2-Tier Data storage: Distributed Relational database and centralized warehouse Telecommunications: high-speed LANs Network: Client/Server, Distributed Middleware IT Personnel: technically skilled, business oriented  Information Systems architecture? Share applications and data within and across functional areas Client/Server db

15. Facilitating Software Systems  Office automation IT for “office” employees Document tracking, communication, scheduling, etc. Client/Server db

16. Facilitating Software Systems (cont’d) Decision Support Systems Provide information to support “semi-structured” decision making  Simon’s model: Intelligence, Design, Choice  At least one of those stages is unstructured, and at least one is structured Effectiveness focus Expert Systems Knowledge-base integrated with DSS Most are “rule-based” systems that process facts, not numbers  Credit evaluation  Cisco tech support Client/Server db

17. Database Approaches  Centralized All data in one location Promotes maintenance and security Subject to single point of failure As size of database grew, performance suffered Broadband still emerging, very expensive Client/Server db

18. Database Approaches  Distributed data management Get data closer to applications Replicated Complete copies in multiple locations Significant overhead Partitioned Each location has portion of database  Data management becomes an issue db Distributed db

19.  Transactions used to interact with a relational “client-server” database For each transaction, OLTP typically deals with a small number of rows from the tables The transactions are typically highly structured, repetitive and have predetermined outcomes E.g., orders, changing customer address, etc. Online Transaction Processing db Distributed db

20. Client/Server Systems Executive Operational Managerial Inbound Logistics Purchasing Raw Materials ProductionFinished Goods Outbound Logistics Sales Functional Transaction Processing System Client/Server System db

21. Network Era (Distributed Computing)  IT Infrastructure (distributed computing environment) Hardware: PCs and high-end Servers Systems Software: Middleware – 3 tiered Data storage: Distributed Relational Database Telecommunications: high-speed WAN Network: Middleware IT Personnel: still technical, but business awareness db Distributed Computing Middleware

22. Introduction of Middleware  Software that makes it possible for systems on different platforms to communicate with each other. Allows applications to talk to each other Consistent Application Program Interface (API) Code application to talk to middleware, not underlying resources Upgrade/modify underlying resources without needing to modify applications db Distributed Computing Middleware

23. Middleware Technologies  Basic types of middleware Transaction Processing Monitor (TP) Object Request Broker (ORB) db Distributed Computing Middleware

24. Transaction Processing Monitor (TP)  TP system: Clients TP Monitor Data Transaction request Transaction Processing db Distributed Computing Middleware

25. TP Monitor (cont’d)  TP is used to build on-line transaction processing (OLTP) systems by coordinating and monitoring the efforts of separate applications.  TP can provide the following: Control transaction applications Provide business logic/rules Database updates db Distributed Computing Middleware

26. Object Request Broker (ORB)  ORB involves synchronous communication and location/platform transparency.  ORB uses object-oriented programming methods. Two standards Distributed Component Object Model (COM)  COM was the Microsoft approach to allow integration of applications on the desktop Common Object Request Broker Architecture (CORBA) db Distributed Computing Middleware

27. ORB (cont’d)  ORB architecture: ORB Client Remote Service (object) locate service activate service establish connection communicate db Distributed Computing Middleware

28. File Sharing  Napster: ORB Request Stored Files locate service activate service establish connection communicate db Distributed Computing Middleware

29. Peer-to-Peer File Sharing  Kazaa: Request Member db Distributed Computing Middleware

30. Advantages of ORB Middleware  Anonymous interaction among applications Integrate new client/server applications with existing legacy, mission-critical applications  Easier development environment Reduce cost Improve time-to-market of applications  Enables distributed data environment  Enables dynamic web applications db Distributed Computing Middleware

31. Disadvantages of ORB Middleware  Switching costs are high Upgrade from previous “Middleware” solutions  Requires high technical expertise Tend to outsource Lengthy deployment time db Distributed Computing Middleware

32. Unresolved Issues with ORB  Security  Scalability Related to network capacity  Rapidly changing technologies db Distributed Computing Middleware

33. DBMS Applications  With advent of high-speed, distributed architectures, expanded our use of database beyond capturing and storing transaction data Knowledge Discovery db Distributed Computing Middleware

34. Knowledge Discovery  What is it: Process of extracting useful knowledge from volumes of data  Supported by three technologies Massive data collection Multiprocessor computing Data mining db Distributed Computing Middleware

35. Massive Data Collection  Business problem: Difficult for larger organizations to analyze organizational data from multiple sources Even with enterprise-wide applications, tend to have distributed databases Solution  Data warehouse db Distributed Computing Middleware

37. Data Warehouse  Collection of data in support of decision making process that is: Subject-oriented: organized by entity, not application Integrated: stored in one place, even though it originated from a variety of sources Crosses functional boundaries of an organization Time-variant: represents a snapshot at one point in time Nonvolatile: data is read-only Typically very large db Distributed Computing Middleware

38. Multidimensional Database  OLTP not good when doing analysis of data – poor performance  OLAP – on-line analytical processing db Distributed Computing Middleware

39. “Slice and Dice” an OLAP Cube

40. Multidimensional Database  OLAP – on-line analytical processing Data stored in arrays – similar to tables Dimensions are the edges of the cube Represent views of business data  Sales Example: product, geography, time Intersection represents sales of specific product, to customers in specific market, on certain date Look for relationships among business elements in database – form basis for the “cubes” db Distributed Computing Middleware

41. Advantages of OLAP  All hierarchical or aggregated values can be pre-calculated in the cube rather than accessing the Warehouse Major reduction in query time  Each cube makes “business sense” Not normalized data structures db Distributed Computing Middleware

42. Multidimensional Database (cont’d)  Data marts Scaled-down version of a data warehouse that focuses on a specific area e.g., a department, a business process db Distributed Computing Middleware

44. Massive Data Analysis  Data mining Provides a means to extract patterns and relationships Example: Analyze sales data to identify products that may be attractive to a customer  Amazon.com buyer suggestions Two capabilities Automated prediction of trends and behaviors Automated discovery of previously unknown patterns Example: Shopping cart analysis db Distributed Computing Middleware

45. Massive Data Analysis  Characteristics of Data Mining Relevant data in large database Typically has client/server architecture Tools integrated with spreadsheets to support analysis  Data Mining Tools Neural computing Intelligent agents Association Analysis db Distributed Computing Middleware

46. Network Enabling Software SupplierCustomer Enterprise Wide Systems Supply Chain Management Customer Relationship Management db Distributed Computing Middleware

47.  IT Infrastructure (Web-enabled) Hardware: Low-end PC with Browser, high-end Servers Systems Software: XML, AJAX,.NET Database: Distributed Relational Network: Use IP-based standards Telecommunications: broadband IT Personnel: Business analysts, technical specialties Internet Era

48. What is the Internet?  Global network of LANs  How did Internet evolve? Originated in 1969, restricted to government, research and education (Arpanet) WWW released in 1992 In 1993: Ban on commercial use lifted Mosaic released Growth (different data depending on source) 3 million in 94 40 million in 97 100 million in 98

49. What are the underlying technologies?  Packet Switching.X25 standard uses packets of 128 bytes Each packet travels independently through network  Protocols: TCP/IP Internet Protocol – destination address Each computer has its own IP address Domain name system (DNS) Transmission Control Protocol – breaks information into data packets

50. What is WWW?  Application that uses the internet Set a standards for storing, retrieving, formatting and displaying information via client/server architecture HTML – standard language  Connection Uniform Resource Locator (URL) Hypertext transport protocol (http) – communication protocol to transfer pages ftp: File Transfer Protocol

51. Business use of the Internet: Electronic Commerce  E-business: Subset of e-commerce Transactions between business partners IndividualEnterprise Supplier/ Customer Internet Intranet Extranet  B2C: Internet  B2B: Extranet  B2E: Intranet

52. Web-based Solutions  Early attempts to incorporate WWW into inter-organizational systems  Static, state-less web pages Complicated navigation Not “connected” to underlying data Page not dynamically updated when data changes

53.  IT Infrastructure (Application Service Providers) Hardware: Web-based Servers, Browsers Software: Object-Oriented Database: Distributed Relational, XML Wrappers Network: Use IP-based standards Telecommunications: wireless IT Personnel: Business Partners, technical specialties Web Services db Web Services

54. Web Service Components WS Directory WS Client WS Provider XML/SOAP/HTTP UDDI UDDI/WSDL db Web Services Dictionary: define what it is and how it works Directory Protocols for exchanging information

55. SOAP  Simple Object Access Protocol Protocol for exchanging XML-based messages using HTTP Uses Remote Procedure Call Works well with network firewalls

56. XML  Extensible Markup Language Way of describing data Provides a text-based means to describe and apply a tree-based structure to information

57. XML  Example from wikipedia Basic bread Flour Yeast Water Salt Mix all ingredients together, and knead thoroughly. Cover with a cloth, and leave for one hour in warm room. Knead again, place in a tin, and then bake in the oven.

58. Web Service Components WS Registry (UDDI, WSDL).Net Enterprise Application Enterprise Integration Server (SOAP processor) Secure TCP/IP Connections SOAP/HTTP Service Requests J2EE SOAP/HTTP JDBC ODBC Web Services Application Server db Web Services

59. J2EE  J2EE 1.4 Standards IBM, Sun and Oracle have compliant offerings Still not the complete solution to build and integrate enterprise applications  But neither is.Net  Do not define: Clustering, reliability, security, application integration, etc. db Web Services

60. Impact of Web Services on CRM  Siebel Systems added support for Simple Object Access Protocol (SOAP), Web Services Description Language, and Java Connectivity Architecture  Oracle supports Java, SOAP, UDDI, and XML.  Epiphany supports SOAP and XML and is planning additional SOAP interfaces to improve integration with third-party applications.  PeopleSoft exposes all application functions to XML db Web Services

61. Hurdles for web services  Standards are evolving, not set  Security  Web services do not 'solve' interoperability between applications Hence – need ERP before you add CRM db Web Services