Chapter 5 IT Infrastructure and Emerging Technologies

IT Infrastructure • Shared technology resources providing platform for specific IS applications • Investment in hardware, software, services (consulting, education, training) • Foundation for serving customers, working with vendors, managing business process • Set of physical devices and software required to operate enterprise • Set of firmwide services o Computing platforms providing computing services (e.g desktop computer, laptop) o Telecommunications services o Data management services (+analyzing) o Application software services (ERP, CRM, SCM, KMS) o Physical facilities management services o IT management (plan infrastr. Coordinate with BU), standards (policies), education (training) , research and development services (future investments) • “Service platform” perspective more accurate view of value of investments

Evolution of IT Infrastructure • General-­‐purpose mainframe & minicomputer era: 1959 to present o 1958 IBM first mainframes introduced (centralized) – support thousands online remote terminals connected o 1965 Less expensive DEC minicomputers (more decentralized) • Personal computer era: 1981 to present o 1981 Introduction of IBM PC o Proliferation in 80s, 90s resulted in growth of personal software o Wintel PC (95%) • Client/server era: 1983 to present o Desktop clients networked to servers, with processing work split between clients and servers o Network may be two-­‐tiered or multitiered (N-­‐tiered) o Various types of servers (network, application, Web) o Smaller, inexpensive machines, costs less, computing power explosion

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Enterprise computing era: 1992 to present o Move toward integrating disparate networks, applications using Internet standards and enterprise applications o Free information flow, link different types of hardware, includes public infrastructures, link applications, web services Cloud and Mobile Computing: 2000 to present o Refers to a model of computing where firms and individuals obtain computing power and software applications over the Internet or other network (shared pool of computing resources) o Fastest growing form of computing

Technology drivers of infrastructure evolution • Moore’s law and microprocessing power o Computing power(2)/microprocessing power (1) doubles every 18 months; the price for computing falls by half every 18 months (3) o Nanotechnology: Shrinks size of transistors to size comparable to size of a virus, width of several atoms • Law of Mass Digital Storage o The amount of data being stored each year doubles o Cost is falling at an exponential rate of 100%/year • Metcalfe’s Law and network economics o Value or power of a network grows exponentially as a function of the number of network members o As network members increase, more people want to use it (demand for network access increases) • Declining communication costs and the Internet o An estimated 1.8 billion people worldwide have Internet access o As communication costs fall toward a very small number and approach 0, utilization of communication and computing facilities explodes à fimrs greatly expand Internet connections, power of their networks… • Technology standards and network effects o Specifications that establish the compatibility of products and the ability to communicate in a network o Unleash powerful economies of scale and result in price declines as manufacturers focus on the products built to a single standard o E.g. Win OS, Microsoft office, Unix (enterprise server), Ethernet, TCP/IP

7 main IT Infrastructure components 1. Computer hardware platforms (Dell, IBM, Sun, HP; Apple, Linux) o Client machines and servers (blade servers: ultrathin computers stored in racks) o Mainframes: IBM mainframe equivalent to thousands of blade servers o Top chip producers: AMD, Intel, IBM o Top firms: IBM, HP, Dell, Sun Microsystems 2. Operating system platforms (Windows – 75% server – 90% clients, Unix + Linux -­‐
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server, Mac OS X, Google Chrome – cloud computing, iOs, Android for handheld devices) 3. Enterprise software applications (SAP, Oracle, middleware provider: BEA, Microsoft)

4. Data management and storage (IBM DB2, Oracle, Microsoft SQL Server, Sybase, MySQL) o Data management software: responsible for organizing/managing data, efficiently accessed and used o Physical Data Storage: EMC Corp. (large scale), Seagate, Maxtor, WD) o Storage area networks (SANs): Connect multiple storage devices on dedicated network 5. Networking/telecommunications platforms (Linux, Novell, Cisco, Alcatel-­‐Lucent) o Telecommunication services (cable, telephones, voice lines, Internet) o Network Operating Systems (Windows Server, Unix …) o Network hardware providers (Cisco, Alcatel…) 6. Internet platforms (Apache, Unix, Cisco, Java) o Hardware, software, management services to support company Web sites, (including Web hosting services) intranets, extranets o Trend to server consolidation, reducing number by increasing power o Internet hardware server market: Dell, HP/Compaq, IBM o Web development tools/suites: Microsoft (FrontPage, .NET) IBM (WebSphere) Sun (Java), independent software developers: Adobe, RealMedia 7. Consulting system integration services (IBM, EDS, Accenture) o Consulting and system integration services o Even large firms do not have resources for a full range of support for new, complex infrastructure o Software integration: ensuring new infrastructure works with legacy systems o Legacy systems: older Transaction Processing Systems created for mainframes that would be too costly to replace or redesign

7 Contemporary Hardware Platform Trends

The emerging mobile digital platform • Cell phones, smartphones with data transmission, web surfing, e-­‐mail, and IM • Netbooks, low-­‐cost lightweight notebooks optimized for wireless communication and core computing tasks • Tablets and networked e-­‐readers Grid computing • Connects geographically remote computers into a single network to combine processing power and create virtual supercomputer • Provides cost savings, speed, agility Virtualization • Allows single physical resource to act as multiple resources (i.e., run multiple instances of OS) • Allows multiple physical resources to appear as a single logical resource • Reduces hardware and power expenditures, facilitates hardware centralization, higher utilization rates Cloud computing • On demand self service obtained over network • Ubiquitous network access using standard network and internet devices • Location independent resource pooling

• Rapid elasticity to meet changing user demand

Measured service, charged for amount of resources used • Infrastructure as a service à use spare capacity e.g. Amazon S3 • Platform as a service à use to develop own applications e.g. IBM, Salesforce.com • Software as a service à use software over network e.g Google Apps • Cloud can be public or private • Allows companies to minimize IT investments (pay what you use = utility computing, on demand computing), more flexibility • Drawbacks: Concerns of security, reliability, dependence Green computing • Practices and technologies for manufacturing, using, disposing of computing and networking hardware to minimize impact on environment • Reducing computer power consumption = high priority (power and cooling) à energy and greenhouse gases Autonomic computing • Industry-­‐wide effort to develop systems that can configure, heal themselves when broken, and protect themselves from outside intruders • Similar to self-­‐updating antivirus software; Apple and Microsoft both use automatic updates High performance, power-­‐saving processors • Multicore processors (chip more processor cores enhancing performance, reduced power consumption, efficient simultaneous processing of multiple tasks)

4 Contemporary Software Platform Trends

Linux and open-­‐source software • Open-­‐source software: Produced by community of programmers, free and modifiable by user • Linux: Open-­‐source software OS, integration, works on all major hardware Software for the Web • Java: Object-­‐oriented programming language, OS and processor-­‐independent, works on all devices,: Java Virtual machine, applets run on a web browser • Ajax: Asynchronous JavaScript and XML, Allows client and server to exchange small pieces of data without requiring the page to be reloaded Web Services • Software components that exchange information using Web standards and languages, regardless of OS or code • XML: Extensible Markup Language, More powerful and flexible than HTML, Tagging allows computers to process data automatically, classifying presentation communication and storage of data • SOAP: Simple Object Access Protocol, Rules for structuring messages enabling applications to pass data and instructions Dollar Rent A Car Webb • WSDL: Web Services Description Language, Framework for describing task Services link performed by Web service and capabilities to other web • UDDI: Universal Description, Discovery, and Integration, Directory for locating sites booking system, no Web services new code • SOA: Service-­‐oriented architecture: set of self-­‐contained services that required communicate with each other to create a working software application, Software developers reuse these services in other combinations to assemble other applications as needed •

Software outsourcing and cloud services Three external sources for software: • Software packages (pre-­‐written, commercially available) and enterprise software (large scale, single integrated worldwide software system) • Software outsourcing (development, maintenance) o Domestic: Primarily for middleware, integration services, software support o Offshore: Primarily for lower level maintenance, data entry, call centers, although outsourcing for new-­‐program development is increasing • Cloud-­‐based software services o Software as a service (SaaS) accessed with Web browser over Internet o Ranges from free or low-­‐cost services for individuals to business and enterprise software

o Users pay on subscription or per-­‐transaction e.g. Salesforce.com o Service Level Agreements (SLAs): formal agreement with service providers, performance measurement, support options • (Web) Mashups: Combinations of two or more online applications, such as combining mapping software (Google Maps) with local content • Apps: Small pieces of software that run on the Internet, on computer, or cell phone, Generally delivered over the Internet o Success of mobile platform depends in lage part on quantity and quality of apps, high switching costs

4 Management Issues

Dealing with platform and infrastructure change • As firms shrink or grow, IT needs to be flexible and scalable • Scalability: Ability to expand to serve larger numbers of users w/o break down • For mobile computing and cloud computing: new policies and procedures for managing, Contractual agreements with firms running clouds and distributing software required (SLA)

Management and governance • Who controls IT infrastructure? • How should IT department be organized? o Centralized: Central IT department makes decisions o Decentralized: Business unit IT departments make own decisions • How are costs allocated between divisions, departments?

Making wise infrastructure investments • Amount to spend on IT is complex question (too much = idle times, too less = no delivering, outperforming competitors à rent vs. buy, security • Total cost of ownership (TCO) model

o Analyzes direct and indirect costs o Hardware, software account for only about 20% of TCO o Other administration costs: Installation, training, support, maintenance, infrastructure, downtime, space and energy o TCO can be reduced through better management, use of cloud services, greater centralization and standardization of hardware and software resources

Competitive forces model for IT infrastructure investment 1. Market demand for firm’s services (inventory of current services meet needs of groups of customers, suppliers, employees, complaining?) 2. Firm’s business strategy (analyze 5 year business strategy, requirement to achieve strategic goals?) 3. Firm’s IT strategy, infrastructure, and cost (TCO analysis, 5 years IT strategy) 4. Information technology assessment (behind or on the bleeding edge to be avoided, standards should be established, multiple cost competing vendors) 5. Competitor firm services (quantitative and qualitative measures to compare) 6. Competitor firm IT infrastructure investments (benchmark expenditures for IT infrastructure)

Chapter 6 Foundations of Business Intelligence: Database and Information Management

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Effective IS provides accurate, timely and relevant information Often: poorly organized and maintained data

File organization concepts • Field: Group of characters as word(s) or number o Describes an entity (person, place, thing on which we store information) o Attribute: Each characteristic, or quality, describing entity • Record: Group of related fields, describing entitiy • File: Group of records of same type

• Database: Group of related files

Problems with traditional file environment • Traditional approach: files maintained separately by different departments with unique data files and own applications • Data redundancy: Presence of duplicate data in multiple files, waste storage res. • Data inconsistency: Same attribute has different values, or names, coding systems • Program-­‐data dependence: When changes in program requires changes to data accessed by program, other programs don’t work anymore • Lack of flexibility, only routine scheduled reports, no ad hoc requests • Poor security, not knowing who has access and changes the data • Lack of data sharing and availability (no trust in accuracy)

Database Approach to Data Management Database • Serves many applications by centralizing data and controlling redundant data using a DBMS Database management system (DBMS) • Software to organize, centralize, manage data efficiently, provide access • Interfaces between applications and physical data files • Separates logical and physical views of data (user don’t need to know where the data actually is stored and organized (physical view), only see the data as they would be perceived (logical view) à available for different logical views • Solves problems of traditional file environment o Controls redundancy by minimizing isolated files o Eliminates inconsistency o Uncouples programs and data o Enables organization to centrally manage data and data security, reducing costs, ad hoc queries Relational DBMS • Keep track of entities, attributes, relationships • Represent data as two-­‐dimensional tables called relations or files • Each table contains data on entity and its attributes • E.g. Microsoft Access = relational DBMS for desktop systems, MySQL Table: grid of columns and rows • Rows (tuples): Records for different entities • Fields (columns): Represents attribute for entity • Key field: Field used to uniquely identify each record,

• Primary key: Field in table used for key fields, cannot be duplicated • Foreign key: Primary key used in second table as look-­‐up field to identify records from original table

Operations of a Relational DBMS (Three basic operations to develop useful sets of data) • SELECT: Creates subset of data of all records that meet stated criteria • JOIN: Combines relational tables to provide user with more information than available in individual tables • PROJECT: Creates subset of columns in table, creating tables with only the information specified

Object-­‐Oriented DBMS (OODBMS) • Stores data and procedures as objects, can be automatically retrieved and shared • Objects can be graphics, multimedia, Java applets, not only structured numbers and characters, integrate from various sources • Relatively slow compared with relational DBMS for processing large numbers of transactions • Hybrid object-­‐relational DBMS: Provide capabilities of both OODBMS and relational DBMS

Databases in the cloud • Typically less functionality than on-­‐premises DBs • Now: used by web-­‐focused start-­‐ups, lower prices • Amazon Web Services (MySQL, license Oracle), Microsoft SQL Azure (integrating with existing software) • Charged based on usage time, volume data stored, input requests, amount read or written • Able to scale computing resources in response to real-­‐time demand, costs low

Capabilities of Database Management Systems • Organize, Manage, Access data in the database • Data definition capability: Specifies structure of database content, used to create tables and define characteristics of fields • Data dictionary: Automated or manual file storing definitions of data elements and their characteristics (name, description, size, type, format, usage, ownership, authorization, security, individuals, business functions, programs, reports) • Data manipulation language: Used to add, change, delete, retrieve data

o Structured Query Language (SQL) o Large/midrange computers: DB2, Oracle, SQL Server employ SQL o Microsoft Access use user-­‐friendly tools of SQL for querying databases • Many DBMS have report generation capabilities for creating polished reports (Crystal Reports = very popular report generator), developing system applications for data entry screens, reports, logic for processing transactions

Designing Databases • Conceptual (logical) design: Abstract model from business perspective • Physical design: How database is arranged on direct-­‐access storage devices • Understand relationship among data, type of data, grouping, usage, changes • Relationships among data elements, redundant database elements • Most efficient way to group data elements to meet business requirements, needs of application programs • Normalization: Streamlining complex groupings of data to minimize redundant data elements and awkward many-­‐to-­‐many relationships (small, stable, flexible data structures) • Enforce referential integrity rules, ensure relationships remain consistent (e.g. no parts from nonexistent suppliers) • Entity-­‐relationship diagram: Used by database designers to document the data model, Illustrates relationships between entities • Distributing databases: Storing database in more than one place • Partitioned: Separate locations store different parts of database • Replicated: Central database duplicated in entirety at different locations

Understand organizations data and how it should be represented in a database to serve business well with your data model, or the data will be inaccurate, incomplete, and difficult to retrieve!

Using Databases to improve business performance and decision-­‐making • Keep track of basic transactions • Provide information to run business more efficiently, make better decisions • Very large databases and systems require special capabilities, tools to analyze large quantities of data, to access data from multiple systems • Data warehousing, data mining, tools for accessing internal databases through web

Data warehousing • Stores current + historical data from many core operational transaction systems • Consolidates and standardizes information for use across enterprise, but data cannot be altered • Data warehouse system will provide query, analysis, and reporting tools • E.g. Catalina Marketing largest loyalty database in the world, US Internal Revenue Service (IRS) with Compliance Data Warehouse consolidating taxpayer data from different resources into relational structure (find out who cheats)

Data marts • Subset of data warehouse, smaller, decentralized • Summarized or highly focused portion of firm’s data for use by specific population of users • Typically focuses on single subject or line of business, constructed more rapidly, lower costs • E.g. Barnes and Noble point-­‐of-­‐sale, college bookstore, online sales

Business Intelligence • Tools for consolidating, analyzing, and providing access to vast amounts of data to help users make better business decisions (patterns, relationships, insights) • Principle tools include: Software for database query and reporting, multidimensional online analytical processing (OLAP), data mining

Online analytical processing (OLAP) • Supports multidimensional data analysis: Viewing data using multiple dimensions, each aspect of information (product, pricing, cost, region, time period) is different dimension • OLAP enables rapid, online answers to ad hoc queries

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Building 3d cubes of data, can be nested within cubes à complex views Either multidimensional database or tool creating multidimensional views in relational databases

Data mining • More discovery driven than OLAP: finds hidden patterns, relationships in large databases and infers rules to predict future behavior • Applications for all functional areas of business, government, scientific work • E.g., Finding patterns in customer data for one-­‐to-­‐one marketing campaigns or to identify profitable customers. • Types of information obtainable from data mining o Associations, occurrences linked to a single event (coke, chips, promotion) o Sequences, events linked over time (house à fridge, oven) o Classification, inferring set of rules, patterns that describe group item belongs (discover characteristics of customers who are likely to leave) o Clustering, similar to classification where no groups defined (partitioning database into groups of customers based on demographics) o Forecasting, use series of existing values to forecast what other values will be (finding patterns to estimate future value of continuous variables) • High level analyses of patterns or trends, can also drill down and provide more detail when needed • Predictive analysis: Uses data mining techniques, historical data, and assumptions about future conditions to predict outcomes of events (e.g. probability a customer will respond to an offer)

Text mining • Extracts key elements from large unstructured data sets (e.g., stored e-­‐mails) • 80% of organizations useful information • Discover patterns, relationships, summarize • New myriad ways unstructured data is generated by consumers and the business uses for this data

Web mining • Discovery and analysis of useful patterns and information from WWW (E.g., to understand customer behavior, evaluate effectiveness of Web site) • Web content mining (Knowledge extracted from content of Web pages) • Web structure mining (E.g., links to and from Web page) • Web usage mining (User interaction data recorded by Web server)

Databases and the Web • Companies use Web to make some internal databases available to customers • Typical configuration includes: o Web server (accessed via web browser, client computer),

o Application server/middleware/CGI scripts (compact program using Common Gateway Interface specification for processing data on a web server), translation HTML to SQL, transfer information, handling all application operations incl. transaction processing, data access btw. Browser and database, takes requests, runs logic process transactions, provides connectivity o Database server (hosting DBM)

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Advantages of using Web for database access: o Ease of use of browser software o Web interface requires few or no changes to database o Inexpensive to add Web interface to system Creating new efficiencies, opportunities, business models

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Managing Data Resources Establishing an information policy • Firm’s rules, procedures, roles for sharing, managing (disseminating, acquiring, classifying, inventorying), standardizing data/information • Specific procedures and accountabilities • Data administration: Firm function responsible for specific policies and procedures to manage data as a corporate organizational resource (develop info policy, planning for data, overseeing logical database design, data dictionary development, monitoring usage) • Data governance: Policies and processes for managing availability, usability, integrity, and security of enterprise data, especially as it relates to government regulations, promoting privacy, security, quality, compliance • Database administration: Defining, organizing, implementing, maintaining database; access rules, security procedures, performed by database design and management group

Ensuring data quality • More than 25% of critical data in Fortune 1000 company databases are inaccurate or incomplete leading to incorrect decisions, product recalls, financial losses • Most data quality problems stem from faulty input, esp. now when companies move business to web and customers/suppliers enter data directly • Before new database in place, need to: o Identify and correct faulty data

o Establish better routines for editing data once database in operation • Data quality audit: Structured survey of the accuracy and level of completeness of the data in an IS (Survey samples/entire from data files, or Survey end users for perceptions of quality) • Data cleansing (scrubbing): Software to detect and correct data that are incorrect, incomplete, improperly formatted, or redundant o Enforces consistency among different sets of data from separate IS