Evolution of Information Technology Infrastructure and Architecture BA 572 - Week 1 – Part 1 Sources: HBR 397 – 118, “Intranets and Middleware” Dr. James Coakley (Oregon State University) MIS Textbook by Turban, Rainer & Potter (Chapter 5) Mr. Sakthi Angappamudali (The Standard) Mr. Lee Martin (Hitachi Consulting) Dr. V.T. Raja (Oregon State University)

BA572 Week 1 (Part 1) Outline IT Infrastructure vs. IT Architecture Evolution of IT Infrastructure and Architecture Major eras of the computer industry Terminology/Acronyms Centralized/Decentralized/Distributed Computing TPS, MIS, DSS, ES, Middleware, OOP, DW, OLAP, Data Mining etc. Comment on Performance Metrics

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

Definitions Information Systems (IS) Architecture: the “plan” that aligns IT infrastructure with business needs Help people effectively fulfill their information needs Note that the term “Information Architecture” is also being used to describe process of designing web sites

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

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

Data Processing Era IT Infrastructure (host-centric processing) Mainframe Data Processing Era IT Infrastructure (host-centric processing) Hardware: Mainframe with text-based terminals Software: Independent functional applications Served one purpose Data Storage: independent “files” for each functional application Telecommunications: Limited support of distributed operations IT Personnel: technically oriented

IS Architecture: Transaction Processing System (TPS) Mainframe 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 Found in all functions of an organization If they fail, the whole organization may suffer Automate “highly structured” decision processes Payroll

IS Architecture: Management Information System (MIS) Mainframe 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 Provide structured information to support decision making Resulted in “Information overload”

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

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

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

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

* Client/Server db 07/16/96 Client/Server Era IT Infrastructure (distributed computing environment) Hardware: PCs and Specialized Servers Software: Facilitating Data storage: Distributed Relational database and centralized warehouse Telecommunications: high-speed LANs Network: Client/Server IT Personnel: technically skilled, business oriented Information Systems architecture? Share applications and data within and across functional areas *

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

Facilitating Software Systems (cont’d) Client/Server db Facilitating Software Systems (cont’d) Decision Support Systems Provide information to support “semi-structured” decision making Effectiveness focus Expert Systems Knowledge-base integrated with DSS Most are “rule-based” systems that process facts, not numbers Credit evaluation Cisco/DELL tech support

Database Approaches Centralized All data in one location Client/Server db Database Approaches Centralized All data in one location Promotes maintenance and security Subject to single point of failure

Database Approaches Distributed data management db Distributed 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 Complex Concurrency Control

Online Transaction Processing db Distributed Online Transaction Processing 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.

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

Network Era (Distributed Computing) * 07/16/96 db Distributed Computing Middleware Network Era (Distributed Computing) IT Infrastructure (distributed computing environment) Hardware: PCs and high-end Servers Software: Enabling, enterprise-wide Data storage: Distributed Relational Database Telecommunications: high-speed WAN Network: Middleware IT Personnel: still technical, but business awareness *

Introduction of Middleware db Distributed Computing 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

Object Request Broker (ORB) db Distributed Computing Middleware Object Request Broker (ORB) ORB involves synchronous communication and location/platform transparency. ORB uses object-oriented programming methods.

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

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

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

Advantages of ORB Middleware db Distributed Computing 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

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

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

Distributed Computing db Distributed Computing Middleware DBMS Applications With advent of high-speed, distributed architectures expanded our use of database beyond capturing and storing transaction data Knowledge Discovery Process of extracting useful knowledge from volumes of data Supported by: Massive data collection (Data Warehouse/Data Marts) Multiprocessor computing On-line Analytical Processing (OLAP)/Data mining

Distributed Computing Data Warehouse db Distributed Computing Middleware 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

Data Warehouse * 07/16/96 Large repository of detailed and summary data used to support the strategic decision making process for the enterprise Stores current and historical data (internal and external) Integrates data from organization’s disparate information systems used by functional units Involve hundreds of gigabytes, and terabytes of data Run on very powerful computers Expensive *

Data Warehousing Process OLTP - Raw Detail No/Minimal History DW-Integrated Scrubbed History Summaries Targeted Specialized (OLAP) OLTP, DW and DM - Data Characteristics Design Mapping OLTP Systems Functional IS External Data Data Mart Central Repository Load Index Aggregation Data Warehouse Extract Scrub Transform End User Workstations Replication Data Set Distribution

Multidimensional Database (cont’d) db Distributed Computing Middleware 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

An Incremental Approach Sales Distribution Product Glossary Customer Marketing Accounts Common Business Metrics Common Business Rules Operations and Inventory Finance Vendors Common Business Dimensions Common Logical Subject Area ERD Individual Architected Data Marts

The Eventual Result Architected Enterprise Foundation Sales Distribution Product Marketing Customer Accounts Finance Operations and Inventory Vendors Enterprise Data Warehouse Architected Enterprise Foundation

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

* 07/16/96 On-line Transaction Processing (OLTP) and On-line Analytical Processing (OLAP) OLTP: Immediate processing/analysis and handling of multiple concurrent transactions from customers/users Example: OLAP: Capability for manipulating and analyzing large volumes of data from multiple perspectives (multidimensional analysis) OLTP – Example: B-C E-Commerce (Amazon.com) OLAP – Example: Product vs. Region vs. Sales *

“Slice and Dice” an OLAP Cube

Distributed Computing db Distributed Computing Middleware 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

Distributed Computing db Distributed Computing Middleware 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

Data Mining Some Benefits: Market Segmentation Fraud Detection * 07/16/96 Data Mining Some Benefits: Market Segmentation Fraud Detection Market Basket Analysis Trend Analysis Market Segmentation: Identify common characteristics of customers who purchase the same products Fraud Detection: Identify which transactions are most likely to be fraudulent Market Basket Analysis: Understanding what products/services are commonly purchased together (e.g, Beer/Diapers) Trend Analysis: Reveals the difference between a typical customer this year versus last year *

Business Intelligence BI/Analytics software (suite): Used to collect, store, analyze and present sufficient and accurate information in a timely manner and in a usable form Includes OLAP, data mining, statistical analysis Has a positive impact on business strategy, and operations Addresses analysis paralysis caused due to information overload?

Business Intelligence Enterprise BI Suites and Platforms

The Decision Making Roadmap Business Planning Actions Vision Knowledge Transaction Systems Decision Support Systems Executive Information Systems? Data Information RUN MANAGE GROW Operational Functional Current Detailed Analyze What If Scenarios History Detailed Multi-Dimensional History Summary Users Knowledge Brokers Management

Network Enabling Software db Distributed Computing Middleware Network Enabling Software Supply Chain Management Customer Relationship Management Enterprise Wide Systems Enterprise Wide Systems Enterprise Wide Systems Supplier Customer

Internet Era IT Infrastructure (Web-enabled) * Internet Era 07/16/96 IT Infrastructure (Web-enabled) Hardware: Low-end PC with Browser, high-end Servers Software: Web extensions Database: Distributed Relational Network: Use IP-based standards Telecommunications: broadband IT Personnel: Business analysts, technical specialties *

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

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 Dynamic and interactive web applications connected to enterprise database(s) Web 2.0 http://www.oreillynet.com/pub/a/oreilly/tim/news/2005/09/30/what-is-web-20.html http://en.wikipedia.org/wiki/Web_2.0

Web Services Standards are evolving Security? db Web Services Web Services Standards are evolving Security? Do web services 'solve' interoperability between applications? Need ERP?

Comment on Performance Metrics * Comment on Performance Metrics 07/16/96 How does IT add value and how much value? TCO/ROI Tangible vs. Intangible Impacts What is(are) purpose(s) of IT applications? Automate Facilitate/Informate Enable business strategy/significant competitive advantage Alignment of IT and Business Strategy “ROI”? *