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Introduction
Perhaps the most important challenge facing information systems is to provide users
with timely and versatile...
Program/Data Dependence
Lack of Flexibility
The information-retrieval capabilities of most traditional systems are limited...
Database Management Systems (ORACLE, SYBASE, MS-SQL, MySQL, NOSQL,
PROGRESS)
It is very important to select a proper progr...
relationship. Each record may have only one parent but an unlimited number of
children. The top record is called the root....
discussed under tree structures, where each course record (for example, course
1) contains the address of the first studen...
Stock-master
Stock-code Stock-name Unit price
3000 ABC AD 20
3001 XYZ AD 100
Depot-master
Depot no Depot name Depot manage...
ERP is the technological backbone of e-business, an enterprise-wide transaction
framework with links into sales order proc...
development phases and change management programs, or trying to do too much
too fast in the conversion process, were typic...
• Retention and loyalty programs
(DATA WAREHOUSE, DATA MINING)
Salesforce.Com, Sugarcrm
SUPPLY CHAIN MANAGEMENT: THE BUSIN...
an example of the almost complete automation of an e-commerce supply chain
process. And EDI over the Internet, using secur...
Decision Support Systems
Decision support systems are computer-based information systems that provide
interactive informat...
Decision support systems use (1) analytical models, (2) specialized databases, (3) a
decision maker’s own insights and jud...
Therefore, DSS are designed to be ad hoc, quick-response systems that are initiated
and controlled by business decision ma...
DSS Packages
Retail: Information Advantage and Unisys offer the Category Management Solution
Suite, an OLAP (OnLine Analyt...
to sales.
Goal-seeking analysis Making repeated changes to selected
variable reaches a target value.
Example: Let’s try in...
them in a document called an RFP (request for proposal) or RFQ (request for
quotation). Then they send the RFP and RFQ to ...
products have become one of the best sources for obtaining up-to-date information
about the experiences of users of the pr...
Notice that there is much more to evaluating hardware than determining the fastest
and cheapest computing device. For exam...
Overall Rating
Evaluating IS services
Most suppliers of hardware and software products and many other firms offer a
variet...
Software
Do they offer a variety of useful e-business software and application packages?
Overall Rating
ASP: Application S...
end users of the proposed systems for possible errors. Of course, testing should not
occur only during the system’s implem...
tester chooses inputs to exercise paths through the code and determine the appropriate outputs.
This is analogous to testi...
supposed to do. It uses external descriptions of the software, including specifications,
requirements, and designs to deri...
Grey-box testing (American spelling: gray-box testing) involves having knowledge of internal
data structures and algorithm...
code is promoted to QA; this strategy is intended to increase the quality of the resulting
software as well as the efficie...
In addition, the software testing should ensure that the portability of the system, as well as
working as expected, does n...
also involve all aspects of the proper use of a new system. In addition, managers and
end users must be educated in how th...
Old System
New System
Conversions can be
• Parallel
• Phased
• Pilot
• Plunge or direct cutover
Conversions can be done on...
errors usually diminish as experience is gained with a new system, they do point out
areas where a system may be improved....
The output of an OLAP query is typically displayed in a matrix (or pivot) format. The dimensions form the rows and
columns...
warehouse, the integrated source data systems and the data warehouse are all integrated since there is no
transformation o...
Big data
From Wikipedia, the free encyclopedia
A visualization created by IBM of Wikipedia edits. At multiple terabytes in...
to reconsider data management options. For others, it may take tens or hundreds of terabytes before data
size becomes a si...
BALANCED SCORECARD
AI: ARTIFICIAL INTELLIGENCE
http://easydiagnosis.com/ expert system
Recommender system
From Wikipedia, ...
2015:
https://www.facebook.com/BigThinkdotcom/videos/1015408123301852/
Data processing in Industrial Systems course notes after week 5
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Data processing in Industrial Systems course notes after week 5

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Data processing in Industrial Systems course notes after week 5

  1. 1. Introduction Perhaps the most important challenge facing information systems is to provide users with timely and versatile access to data stored in computer files. In a dynamic business environment there are many unanticipated needs for information. Often the basic underlying data satisfy these information needs are contained in computer files but cannot be accessed and output in a suitable format on a timely basis. Database management systems have the potential to meet this challenge. Traditional Approach to Information Processing Data Redundancy Data redundancy increases data editing, maintenance, and storage costs. In addition, data stored on two master files (which should in theory be identical) are often different for good reason, but such differences inevitably create confusion. Lack of Data Integration To change a file structure (e.g.: add a new field) in a traditional programming language like COBOL • Make a new file with new field old file structure • Copy data from old file in to new file • Delete old file • Rename new file as old file’s name A B copy Old file New file (extended fields) Delete A B A Rename A Delete A
  2. 2. Program/Data Dependence Lack of Flexibility The information-retrieval capabilities of most traditional systems are limited to predetermined requests for data. Therefore, the system produces information in the form of scheduled reports and queries which it has been previously programmed to handle. If management needs unanticipated data, the information can perhaps be provided if it is in the files of the system. Extensive programming is often involved. Thus, by the time the programming is completed, the information may no longer be required or useful. This problem has long plagued information systems. Management knows that a particular piece of information can be produced on a one-time basis, but the expense and time involved are generally prohibitive. Ideally, information processing should be able to mix related data elements from several different files and produce information with a fast turnaround to service unanticipated requests for information. Name Surname Tel.No Name Surname Tel.No Birth Day New File Old File
  3. 3. Database Management Systems (ORACLE, SYBASE, MS-SQL, MySQL, NOSQL, PROGRESS) It is very important to select a proper programming tool when building a MIS. A DBMS should be: • Effective • Fast • Easy to communicate to other DBMSs. • Cheap • Safe (reliable) • Good security functions • Upgrade utilities (an old version program working with new ones) -immigration • Independent to hardware (after preparing a program with your IBM compatible PC, it should be working in a Unix operating system platform) Case study: In a big Turkish company • Marketing department enter customer orders to the computer • They print out the customer orders and give this report to production planning department. • Production planning department reenter these data to their database for planning. Logical Data-Base Structures Logical Data-Base Structures Two key features of a DBMS are the ability to reduce data redundancy and the ability to associate related data elements such as related fields and records. These functions are accomplished through the use of keys, embedded pointers, and linked lists. Tree Structures Figure illustrates student data in a tree (hierarchical) structure. The lower part of the figure shows the data fields in each record. A tree structure consists of records (often called segments) that are linked to related records in a one-to-many
  4. 4. relationship. Each record may have only one parent but an unlimited number of children. The top record is called the root. As shown in figure, each student can attend many semesters and take many courses in each semester. However, each course is tied to a single semester, and the data in each semester record are in turn tied to a single student. Figure: A tree structure (Example: product tree, bill of materials) Fields in the student record Fields in the semester record Fields in the Course Record Network Structures A network structure allows many-to-many relationship among the nodes in the structure. Figure illustrates a network structure between courses and students. Each student can enroll in several classes, each class has many students. The physical storage as well as data linkage in a network structure involve embedded pointers in each record as in a tree structure. There are several schemes for using pointers with network structures. One is similar to the scheme CAR 307 STUDENT ENGINE-FALL ELECTRICAL SYST. SPRING VALVES Course record ENG1020 Course record ACCT2111 Course record MSCI2011 Student Number Student Name Addres s To-Date Grade-Point Average Date Admitte d Major Semeste r Semeste r Fees Fees Paid Semester Grade-Point Average Course Number Course Grade
  5. 5. discussed under tree structures, where each course record (for example, course 1) contains the address of the first student in the course, and then the first student record, in turn, contains the address of the second student in the course, and so on, thereby forming a linked list. Relational Structures Most business data have traditionally been organized in the form of simple tables with only columns and rows. In a relational DBMS, these tables are called relations. This data structure is known as the relational model, since it is based on mathematical theory of relations. One of the greatest advantages of relational model is its conceptual simplicity. The relational or tabular model of data is used in a large variety of applications, ranging from your weekly shopping list to the annual report of the world’s largest corporation. Most people are familiar with the relational model as table. But the relational model does use some unfamiliar terminology. What we have come to know as a file is called either a table or relation. Each row in the table is called a tuple (rhymes with couple). A tuple is the same as a record in regular file terminology. The columns of the table are known as attributes and they are equivalent to fields within records. Instead of using the formal relational terminology of relations, tuples, and attributes we will use the more familiar files, records, and fields as do most real-world relational database systems.
  6. 6. Stock-master Stock-code Stock-name Unit price 3000 ABC AD 20 3001 XYZ AD 100 Depot-master Depot no Depot name Depot manager 1 İSTANBUL AD 2 ANKARA UC Stock-status Stock-code Depot no Quantity 3000 1 300 3001 2 200 3001 3 50 3001 4 10 Materials inventory weekly Report Stock Code Stock Name Depot No Depot Name Quantity Unit Price Amount 3000 ABC 1 İstanbul 300 AD 20 6,000 3001 XYZ 2 Ankara 200 AD 100 20,000 3001 XYZ 3 Yalova 50 AD 100 5,000 3001 XYZ 4 İzmit 10 AD 100 1,000 Enterprise Resource Planning: The Business Backbone What is ERP?
  7. 7. ERP is the technological backbone of e-business, an enterprise-wide transaction framework with links into sales order processing, inventory management and control, production and distribution planning, and finance. Benefits and challenges of ERP ERP systems can generate significant business benefits for a company. Many other companies have found major business value in their use of ERP in several basic ways: • Quality and efficiency: ERP creates a framework for integrating and improving a company’s internal business processes that result in significant improvements in the quality and efficiency of customer service, production, and distribution. • Decreased costs: Many companies report significant reductions in transaction processing costs and hardware, software, and IT support staff compared to the nonintegrated legacy systems that were replaced by their new ERP systems. • Decision support: ERP provides vital cross-functional information on business performance quickly to managers to significantly improve their ability to make better decisions in a timely manner across the entire business enterprise. • Enterprise agility: Implementing ERP systems breaks down many former departmental and functional walls or “silos” of business processes, information systems, and information resources. This results in more flexible organizational structures, managerial responsibilities, and work roles, and therefore a more agile and adaptive organization and workforce that can more easily capitalize on new business opportunities. Causes of ERP failures What have been the major causes of failure in ERP projects? In almost every case, the business managers and IT professionals of these companies underestimated the complexity of the planning, development, and training that were needed to prepare for a new ERP system that would radically change their business processes and information systems. Failure to involve affected employees in the planning and
  8. 8. development phases and change management programs, or trying to do too much too fast in the conversion process, were typical causes of failed ERP projects. Insufficient training in the new work tasks required by the ERP system, and failure to do enough data conversion and testing, were other causes of failure. In many cases, ERP failures were also due to over-reliance by company or IT management on the claims of ERP software vendors or the assistance of prestigious consulting firms hired to lead the implementation. The following experiences of companies that did it right give us a helpful look at what is needed for a successful ERP implementation. ERP - 2.ppt sap 1.ppt Trends in ERP Today, ERP is still evolving – adapting to developments in technology and the demands of the market. Four important trends are shaping ERP’s continuing evolution: improvements in integration and flexibility, extensions to e-business applications, a broader reach to new users, and the adoption of Internet technologies. (B2B: BUSINESS TO BUSINESS, B2C: BUSINESS TO CUSTOMERS/CONSUMERS) Customer Relationship Management: The Business Focus What is CRM? Managing the full range of the customer relationship involves two related objectives: one, to provide the organization and all of its customer-facing employees with a single, complete view of every customer at every touch point and across all channels; and, two, to provide the customer with a single, complete view of the company and its extended channels. Major application components of a CRM system: • Contact and account management • Sales • Marketing and fulfillment • Customer service and support • The performance of marketing & sales personnel
  9. 9. • Retention and loyalty programs (DATA WAREHOUSE, DATA MINING) Salesforce.Com, Sugarcrm SUPPLY CHAIN MANAGEMENT: THE BUSINESS NETWORK What is SCM? Legacy supply chains are clogged with unnecessary steps and redundant stockpiles. For instance, a typical box of breakfast cereal spends an incredible 104 days getting from factory to supermarket, struggling its way through an unbelievable maze of wholesalers, distributors, brokers, and consolidators, each of which has a warehouse. The e-commerce opportunity lies in the fusing of each company’s internal system to those of its suppliers, partners, and customers. This fusion forces companies to better integrate inter-enterprise supply chain processes to improve manufacturing efficiency and distribution effectiveness. Unilever Beer Game (trick) www.masystem/beergame book order by using amazon.com GM & TOYOTA # OF PURCHASING DEPT. PERSONNEL ERP DSS-8-SC-ERP.ppt MRP : MATERIALS REQUIREMENT PLANNING MRP II: MANUFACTURING RESOURCES PL. Electronic Data Interchange Electronic data interchange (EDI) was one of the earliest uses of information technology for supply chain management. EDI involves the electronic exchange of business transaction documents over the Internet and other networks between supply chain trading partners (organizations and their customers and suppliers). Data representing a variety of business transaction documents (such as purchase orders, invoices, requests for quotations, and shipping notices) are automatically exchanged between computers using standard document message formats. Typically, EDI software is used to convert a company’s own document formats into standardized EDI formats as specified by various industry and international protocols. Thus, EDI is
  10. 10. an example of the almost complete automation of an e-commerce supply chain process. And EDI over the Internet, using secure virtual private networks, is a growing B2B e-commerce application. Figure: The supply chain management functions and potential benefits offered by the SCM module in the mySAP e-business software suite. SCM Functions Planning Supply chain design • Optimize network of suppliers, plants, and distribution centers Collaborative demand and supply planning • Develop an accurate forecast of customer demand by sharing demand and supply forecasts instantaneously across multiple tiers • Internet-enable collaborative scenarios, such as collaborative planning, forecasting, and replenishment (CPFR), and vendor- managed inventory Execution Materials management • Share accurate inventory and procurement order information • Ensure materials required for production are available in the place at the right time • Reduce raw material spending, procurement costs, safety stocks, and raw material and finished goods inventory Collaborative manufacturing • Optimize plans and schedules while considering resource, material, and dependency constraints Collaborative fulfillment • Commit to delivery dates in real time • Fulfill orders from all channels on time with order management, transportation planning, and vehicle scheduling • Support the entire logistics process, including picking, packing, shipping and delivery in foreign countries Supply chain event management • Monitor every stage of the supply chain process, form price quotation to the moment the customer receives the product, and receive alerts when problems arise Supply chain performance management • Report key measurements in the supply chain, such as filling rates, order cycle times, and capacity utilization Trends in SCM The supplier-facing applications arena will see the continued growth of public as well as private networks that transform linear and inflexible supply chains into nonlinear and dynamic fulfillment networks. Supplier-facing applications will also evolve along another dimension: from automation and integration of supply chains to collaborative sourcing, planning, and design across their supplier networks. Figure: Stages in the use of supply chain management
  11. 11. Decision Support Systems Decision support systems are computer-based information systems that provide interactive information support to managers and business professionals during the decision-making process. Information Sharing, Product/Sales Data Sourcing Help Logistics, Order Fulfillment Order Management, Inventory Management, Resource Allocation Systems Use and Integration Collaborative Marketing, Sales and Service SCM Optimization, Collaborative Design and Delivery SCM Stage 1 Current supply chain improvement Supply chain, e-commerce loosely coupled SCM Stage 2 Intranet/extranet links to trading partners Supplier network expansion SCM Stage 3 Collaborative planning and fulfillment Extranet and exchange- based collaboration
  12. 12. Decision support systems use (1) analytical models, (2) specialized databases, (3) a decision maker’s own insights and judgments, and (4) an interactive, computer- based modeling process to support the making of semi-structured and unstructured business decisions. See Figure: Comparing decision support systems and management information systems Example: An example might help at this point. Sales managers typically rely on management information systems to produce sales analysis reports. These reports contain sales performance figures by product line, salesperson, sales region, and so on. A decision support system, on the other hand, would also interactively show a sales manager the effects performance of changes in variety of factors (such as promotion expense and salesperson compensation). The DSS could use several criteria (such as expected gross margin and market share) to evaluate and rank several alternative combinations of sales performance factors Figure: Comparing decision support systems and management information systems. Management Information Systems Decision Support Systems Decision support provided Provide information about the performance of the organization Provide information and decision support techniques to analyze specific problems or opportunities Information form and frequency Periodic, exception, demand, and push reports and responses Interactive inquiries and responses Information format Pre-specified, fixed format Ad hoc, flexible, and adaptable format Information processing methodology Information produced by extraction and manipulation of business data Information produced by analytical modeling of business data.
  13. 13. Therefore, DSS are designed to be ad hoc, quick-response systems that are initiated and controlled by business decision makers. Decision support systems are thus able to directly support the specific types if decision and the personal decision- making styles and needs of individual executives, managers, and business professionals. DSS Components Unlike management information systems, decision support systems rely on model bases as well as databases as vital system resources. A DSS model base is a software component that consists of models used in computational and analytical routines that mathematically express relationships among variables. For example, a spreadsheet program might contain models that express simple accounting relationships among variables such as Revenue – Expenses = Profit. Or a DSS model base could include models and analytical techniques used to express much more complex relationships. For example, it might contain linear programming models, multiple regression forecasting models, and capital budgeting present value models. Such models may be stored in the form of spreadsheet models or templates, or statistical and mathematical programs and program modules. DSS software packages can combine model components to create integrated models that support specific types of decisions. DSS software typically contains built-in analytical modeling routines and also enables you to build your own models. Many DSS packages are now available in microcomputer and Web-enables versions. Of course, electronic spreadsheet packages also provide some of the model building (spreadsheet models) and analytical modeling (what-if and goal- seeking analysis) offered by more powerful DSS software.
  14. 14. DSS Packages Retail: Information Advantage and Unisys offer the Category Management Solution Suite, an OLAP (OnLine Analytical Processing) decision support system and industry-specific data model. Insurance: Computer Associates offers RiskAdvisor, an insurance risk decision support system whose data model stores information in insurance industry specific tables designed for optimal query performance. Telecom: NCR and SABRE Decision Technologies have joined forces to create the NCR Customer Retention program for the communications industry including data marts for telephone companies to use for decision support in managing customer loyalty, quality of service, network management, fraud, and marketing. Using Decision Support Systems Using a decision support system involves an interactive analytical modeling process. For example, using a DSS software package for decision support may result in a series of displays in response to alternative what-if changes entered by the manager. This differs from the demand responses of management information systems, since decision makers are not demanding prespecified information. Rather, they are exploring possible alternatives. Thus, they do not have to specify their information needs in advance. Instead, they use the DSS to find the information they need to help them make a decision. That is the essence of the decision support system concept. Figure: Activities and examples of the major types of analytical modeling Type of Analytical Modeling Activities and Examples What-if analysis Observing how changes to selected variables affect other variables. Example: What if we cut advertising by 10%? What would happen to sales? Sensitivity analysis Observing how repeated changes to a single variable affect other variables. Example: Let’s cut advertising by $1000 repeatedly so we can see its relationship
  15. 15. to sales. Goal-seeking analysis Making repeated changes to selected variable reaches a target value. Example: Let’s try increases in advertising until sales reach $1 million. Optimization analysis Finding an optimum value for selected variables, given certain constraints. Example: What’s the best amount of advertising to have, given our budget and choice of media? Using a decision support system involves four basic types of analytical modeling activities: (1) what-if analysis, (2) sensitivity analysis, (3) goal-seeking analysis, and (4) optimization analysis. Let’s briefly look at each type of analytical modeling that can be used for decision support. See Figure: Activities and examples of the major types of analytical modeling. Executive Information Systems Executive information systems (EIS) are information systems that combine many of the features of management information systems and decision support systems. When they were first developed, their focus was on meeting the strategic information needs of top management. Thus, the first goal of executive information systems was to provide top executives with immediate easy access to information about a firm’s critical success factors (CSFs), that is, key factors that are critical to accomplishing an organization’s strategic objectives. For example, the executives of a retail store chain would probably consider factors such as its e-commerce versus traditional sales results, or its product line mix to be critical to its survival and success. Implementing Business Systems Evaluating hardware, software, and services How do companies evaluate and select hardware, software and IT services, such as those shown in the Figure? Large companies may require suppliers to present bids and proposals based on system specifications developed during the design stage of systems development. Minimum acceptable physical and performance characteristics and all government agencies formalize these requirements by listing
  16. 16. them in a document called an RFP (request for proposal) or RFQ (request for quotation). Then they send the RFP and RFQ to appropriate vendors, who use it as the basis for preparing a proposed purchase agreement. Companies may use a scoring system of evaluation when there are several competing proposals for a hardware or software acquisition. They give each evaluation factor a certain number of maximum possible points. Then they assign each competing proposal points for each factor, depending on how well it meets the user’s specifications. Scoring evaluation factors for several proposals helps organize and document the evaluation process. It also spotlights the strengths and weaknesses of each proposal. Another method for selecting is AHP: http://www.ufukcebeci.com/EditModule.aspx?tabid=42&mid=44&def=News %20Article%20View&ItemId=7 YOU PLAN TO OPEN A PIZZA RESTAURANT . DEFINE HARDWARE, SOFTWARE AND MIS & SUBMODULES NEEDED. Figure: An example of the implementation process activities and time lines for a company installing an intranet-based employee benefits system in its human resource management department. Intranet Implementation Activities Month 1 Month 2 Month 3 Month 4 Acquire and install server hardware and software Train administrators Acquire and install browser software Acquire and install publishing software Train benefits employees on publishing software Convert benefits manuals and add revisions Create Web-based tutorials for the intranet Hold rollout meetings Whatever the claims of hardware manufacturers and software suppliers, the performance of hardware and software must be demonstrated and evaluated. Independent hardware and software information services (such as Datapro and Auerbach) may be used to gain detailed specification information and evaluations. Other users are frequently the best source on information needed to evaluate the claims of manufacturers and suppliers. That’s why Internet newsgroups established to exchange information about specific software or hardware vendors and their
  17. 17. products have become one of the best sources for obtaining up-to-date information about the experiences of users of the products. Large companies frequently evaluate proposed hardware and software by requiring the processing of special benchmark test programs and test data. Benchmarking simulates the processing of typical jobs on several computers and evaluates their performances. Users can then evaluate test results to determine which hardware device or software package displayed the best performance characteristics. Hardware evaluation factors When you evaluate the hardware needed by a new business application, you should investigate specific physical and performance characteristics for each computer system or peripheral component to be acquired. Specific questions must be answered concerning many important factors. Ten of these hardware evaluation factors and questions are summarized in the figure. Figure: A summary of ten major hardware evaluation factors. Hardware Evaluation Factors Rating Performance What are the speed, capacity, and throughput? Cost What is its lease or purchase price? What will be its cost of operations and maintenance? Reliability What are the risk of malfunction and its maintenance requirements? What are its error control and diagnostic features? Compatibility Is it compatible with existing hardware and software? Is it compatible with hardware and software provided by competing suppliers? Technology In what year of its product life cycle is it? Does it use a new untested technology or does it run the risk of obsolescence? Ergonomics Has it been “human factors engineered” with the user in mind? Is it user-friendly, designed to be safe, comfortable, and easy to use? Connectivity Can it be easily connected to wide area and local area networks that use different types of network technologies and bandwidth alternatives? Scalability Can it handle the processing demands of a wide range of end users, transactions, queries, and other information processing requirements? Software Is the system and application software available that can best use this hardware? Support Are the services required to support and maintain it available? Overall Rating
  18. 18. Notice that there is much more to evaluating hardware than determining the fastest and cheapest computing device. For example, the question of obsolescence must be addressed by making a technology evaluation. The factor of ergonomics is also very important. Ergonomic factors ensure that computer hardware and software are user- friendly, that is, safe, comfortable, and easy to use. Connectivity is another important evaluation factor, since so many network technologies and bandwidth alternatives are available to connect computer systems to the Internet, intranet, and extranet networks. Software evaluation factors You should evaluate software according to many factors that are similar to those used for hardware evaluation. Thus, the factors of performance, cost, reliability, availability, compatibility, modularity, technology, ergonomics, and support should be used to evaluate proposed software acquisitions. In addition, however, the software evaluation factors summarized in figure must also be considered. You should answer the questions they generate in order to properly evaluate software purchases. For example, some software packages are notoriously slow, hard to use, bug-filled, or poorly documented. They are not good choice, even if offered at attractive prices. Figure: A summary of ten major software evaluation factors. Software Evaluation Factors Rating Quality Is it bug-free, or does it have many errors in its program code? Efficiency Is the software a well-developed system of program code that does not use much CPU time, memory capacity, or disk space? Flexibility Can it handle our e-business processes easily, without major modification? Security Does it provide control procedures for errors, malfunctions, and improper use? Connectivity Is it Web-enabled so it can easily access the Internet, intranets, and extranets, on its own, or by working with Web browsers or other network software? Language Is it written in a programming language that is familiar to our own software developers? Documentation Is the software well documented? Does it include help screens and helpful software agents? Hardware Does existing hardware have the features required to best use this software? Other factors What are its performance, cost, reliability, availability, compatibility, modularity, technology, ergonomics, scalability, and support characteristics?
  19. 19. Overall Rating Evaluating IS services Most suppliers of hardware and software products and many other firms offer a variety of IS services to end users and organizations. Examples include assistance during e-commerce website development, installation or conversion of new hardware and software, employee training, and hardware maintenance. Some of these services are provided without cost by hardware manufacturers and software suppliers. Other types of IS services needed by a business can be outsourced to an outside company for a negotiated price. For example, systems integrators take over complete responsibility for an organization’s computer facilities when an organization outsources its computer operations. They may also assume responsibility for developing and implementing large systems development projects that involve many vendors and subcontractors. Value-added resellers (VARs) specialize in providing industry-specific hardware, software, and services from selected manufacturers. Many other services are available to end users, including systems design, contract programming, and consulting services. Evaluation factors and questions for IS services are summarized in the figure. Figure: Evaluation factors for IS services. Evaluation Factors for IS Services Rating Performance What has been their past performance in view of their past promises? Systems development Are website and other e-business developers available? What are their quality and cost? Maintenance Is equipment maintenance provided? What are its quality and cost? Conversion What systems development and installation services will they provide during the conversion period? Training Is the necessary training of personnel provided? What are its quality and cost? Backup (timed backup) Are similar computer facilities available nearby for emergency backup purposes? Accessibility Does the vendor provide local or regional sites that offer sales, systems development, and hardware maintenance services? Is a customer support center at the vendor’s website available? Is a customer hot line provided? Business position Is the vendor financially strong, with good industry market prospects? Hardware Do they provide a wide selection of compatible hardware devices and accessories?
  20. 20. Software Do they offer a variety of useful e-business software and application packages? Overall Rating ASP: Application Service Provider Other implementation activities  How to design forms: DESIGN A PURCHASING (CUSTOMER) ORDER FORM  How to code materials: • Code must be unique. • First use main groups, Then the sub groups • Code considering extentions in time for material/product. (Code should be open-ended) • Don’t use /,:, %, ; and other specific characters • Don’t use roman characters (XII, V) • If the code is too long, it is hard to remember (TALKING CODES) • If possible, use national and int. compatible standards such as barcodes, etc. DE 31030, FE 43002 BAR CODE CONTROL: 100315421004 3 1+0+0+3…. = 21  2+1 = 3 Testing, documentation, and training are the keys to successful implementation of a new business system. Testing System testing may involve testing website performance, testing and debugging software, and testing new hardware. An important part of testing is the review of prototypes of displays, reports, and other output. Prototypes should be reviewed by
  21. 21. end users of the proposed systems for possible errors. Of course, testing should not occur only during the system’s implementation stage, but throughout the system’s development process. For example, you might examine and critique prototypes of input documents, screen displays, and processing procedures during the systems design stage. Immediate end user testing is one of the benefits of a prototyping process. They say 30 % of software in NASA is written in FORTRAN. If it works, don’t touch. Software testing Testing methods[edit] Static vs. dynamic testing[edit] There are many approaches available in software testing. Reviews, walkthroughs, or inspections are referred to as static testing, whereas actually executing programmed code with a given set of test cases is referred to as dynamic testing. Static testing is often implicit, as proofreading, plus when programming tools/text editors check source code structure or compilers (pre-compilers) check syntax and data flow as static program analysis. Dynamic testing takes place when the program itself is run. Dynamic testing may begin before the program is 100% complete in order to test particular sections of code and are applied to discrete functions or modules. Typical techniques for this are either using stubs/drivers or execution from a debugger environment. Static testing involves verification, whereas dynamic testing involves validation. Together they help improve software quality. Among the techniques for static analysis, mutation testing can be used to ensure the test cases will detect errors which are introduced by mutating the source code. The box approach[edit] Software testing methods are traditionally divided into white- and black-box testing. These two approaches are used to describe the point of view that a test engineer takes when designing test cases. White-box testing[edit] Main article: White-box testing White-box testing (also known as clear box testing, glass box testing, transparent box testing and structural testing, by seeing the source code) tests internal structures or workings of a program, as opposed to the functionality exposed to the end-user. In white-box testing an internal perspective of the system, as well as programming skills, are used to design test cases. The
  22. 22. tester chooses inputs to exercise paths through the code and determine the appropriate outputs. This is analogous to testing nodes in a circuit, e.g. in-circuit testing (ICT). While white-box testing can be applied at the unit, integration and system levels of the software testing process, it is usually done at the unit level. It can test paths within a unit, paths between units during integration, and between subsystems during a system–level test. Though this method of test design can uncover many errors or problems, it might not detect unimplemented parts of the specification or missing requirements. Techniques used in white-box testing include: • API testing – testing of the application using public and private APIs (application programming interfaces) • Code coverage – creating tests to satisfy some criteria of code coverage (e.g., the test designer can create tests to cause all statements in the program to be executed at least once) • Fault injection methods – intentionally introducing faults to gauge the efficacy of testing strategies • Mutation testing methods • Static testing methods Code coverage tools can evaluate the completeness of a test suite that was created with any method, including black-box testing. This allows the software team to examine parts of a system that are rarely tested and ensures that the most important function points have been tested. [22] Code coverage as a software metric can be reported as a percentage for: • Function coverage, which reports on functions executed • Statement coverage, which reports on the number of lines executed to complete the test • Decision coverage, which reports on whether both the True and the False branch of a given test has been executed 100% statement coverage ensures that all code paths or branches (in terms of control flow) are executed at least once. This is helpful in ensuring correct functionality, but not sufficient since the same code may process different inputs correctly or incorrectly. Black-box testing[edit] Main article: Black-box testing Black box diagram Black-box testing treats the software as a "black box", examining functionality without any knowledge of internal implementation, without seeing the source code. The testers are only aware of what the software is supposed to do, not how it does it.[23] Black-box testing methods include: equivalence partitioning, boundary value analysis, all-pairs testing, state transition tables, decision table testing, fuzz testing, model-based testing, use casetesting, exploratory testing and specification-based testing. Specification-based testing aims to test the functionality of software according to the applicable requirements.[24] This level of testing usually requires thorough test cases to be provided to the tester, who then can simply verify that for a given input, the output value (or behavior), either "is" or "is not" the same as the expected value specified in the test case. Test cases are built around specifications and requirements, i.e., what the application is
  23. 23. supposed to do. It uses external descriptions of the software, including specifications, requirements, and designs to derive test cases. These tests can be functional or non- functional, though usually functional. Specification-based testing may be necessary to assure correct functionality, but it is insufficient to guard against complex or high-risk situations.[25] One advantage of the black box technique is that no programming knowledge is required. Whatever biases the programmers may have had, the tester likely has a different set and may emphasize different areas of functionality. On the other hand, black-box testing has been said to be "like a walk in a dark labyrinth without a flashlight."[26] Because they do not examine the source code, there are situations when a tester writes many test cases to check something that could have been tested by only one test case, or leaves some parts of the program untested. This method of test can be applied to all levels of software testing: unit, integration, system and acceptance. It typically comprises most if not all testing at higher levels, but can also dominate unit testing as well. Visual testing[edit] The aim of visual testing is to provide developers with the ability to examine what was happening at the point of software failure by presenting the data in such a way that the developer can easily find the information she or he requires, and the information is expressed clearly.[27][28] At the core of visual testing is the idea that showing someone a problem (or a test failure), rather than just describing it, greatly increases clarity and understanding. Visual testing therefore requires the recording of the entire test process – capturing everything that occurs on the test system in video format. Output videos are supplemented by real-time tester input via picture-in-a-picture webcam and audio commentary from microphones. Visual testing provides a number of advantages. The quality of communication is increased drastically because testers can show the problem (and the events leading up to it) to the developer as opposed to just describing it and the need to replicate test failures will cease to exist in many cases. The developer will have all the evidence he or she requires of a test failure and can instead focus on the cause of the fault and how it should be fixed. Visual testing is particularly well-suited for environments that deploy agile methods in their development of software, since agile methods require greater communication between testers and developers and collaboration within small teams.[citation needed] Ad hoc testing and exploratory testing are important methodologies for checking software integrity, because they require less preparation time to implement, while the important bugs can be found quickly. In ad hoc testing, where testing takes place in an improvised, impromptu way, the ability of a test tool to visually record everything that occurs on a system becomes very important in order to document the steps taken to uncover the bug.[clarification needed] [citation needed] Visual testing is gathering recognition in customer acceptance and usability testing, because the test can be used by many individuals involved in the development process.[citation needed] For the customer, it becomes easy to provide detailed bug reports and feedback, and for program users, visual testing can record user actions on screen, as well as their voice and image, to provide a complete picture at the time of software failure for the developers. Further information: Graphical user interface testing Grey-box testing[edit] Main article: Gray box testing
  24. 24. Grey-box testing (American spelling: gray-box testing) involves having knowledge of internal data structures and algorithms for purposes of designing tests, while executing those tests at the user, or black-box level. The tester is not required to have full access to the software's source code.[29][not in citation given] Manipulating input data and formatting output do not qualify as grey- box, because the input and output are clearly outside of the "black box" that we are calling the system under test. This distinction is particularly important when conducting integration testing between two modules of code written by two different developers, where only the interfaces are exposed for test. However, tests that require modifying a back-end data repository such as a database or a log file does qualify as grey-box, as the user would not normally be able to change the data repository in normal production operations.[citation needed] Grey-box testing may also include reverse engineeringto determine, for instance, boundary values or error messages. By knowing the underlying concepts of how the software works, the tester makes better- informed testing choices while testing the software from outside. Typically, a grey-box tester will be permitted to set up an isolated testing environment with activities such as seeding a database. The tester can observe the state of the product being tested after performing certain actions such as executing SQL statements against the database and then executing queries to ensure that the expected changes have been reflected. Grey-box testing implements intelligent test scenarios, based on limited information. This will particularly apply to data type handling, exception handling, and so on.[30] Testing levels[edit] There are generally four recognized levels of tests: unit testing, integration testing, component interface testing, and system testing. Tests are frequently grouped by where they are added in the software development process, or by the level of specificity of the test. The main levels during the development process as defined by the SWEBOK guide are unit-, integration-, and system testing that are distinguished by the test target without implying a specific process model.[31] Other test levels are classified by the testing objective.[31] There are two different levels of tests from the perspective of customers: low-level testing (LLT) and high-level testing (HLT). LLT is a group of tests for different level components of software application or product. HLT is a group of tests for the whole software application or product.[citation needed] Unit testing[edit] Main article: Unit testing Unit testing, also known as component testing, refers to tests that verify the functionality of a specific section of code, usually at the function level. In an object-oriented environment, this is usually at the class level, and the minimal unit tests include the constructors and destructors.[32] These types of tests are usually written by developers as they work on code (white-box style), to ensure that the specific function is working as expected. One function might have multiple tests, to catch corner cases or other branches in the code. Unit testing alone cannot verify the functionality of a piece of software, but rather is used to ensure that the building blocks of the software work independently from each other. Unit testing is a software development process that involves synchronized application of a broad spectrum of defect prevention and detection strategies in order to reduce software development risks, time, and costs. It is performed by the software developer or engineer during the construction phase of the software development lifecycle. Rather than replace traditional QA focuses, it augments it. Unit testing aims to eliminate construction errors before
  25. 25. code is promoted to QA; this strategy is intended to increase the quality of the resulting software as well as the efficiency of the overall development and QA process. Depending on the organization's expectations for software development, unit testing might include static code analysis, data-flow analysis, metrics analysis, peer code reviews, code coverage analysis and other software verification practices. Integration testing[edit] Main article: Integration testing Integration testing is any type of software testing that seeks to verify the interfaces between components against a software design. Software components may be integrated in an iterative way or all together ("big bang"). Normally the former is considered a better practice since it allows interface issues to be located more quickly and fixed. Integration testing works to expose defects in the interfaces and interaction between integrated components (modules). Progressively larger groups of tested software components corresponding to elements of the architectural design are integrated and tested until the software works as a system.[33] Component interface testing[edit] The practice of component interface testing can be used to check the handling of data passed between various units, or subsystem components, beyond full integration testing between those units.[34][35] The data being passed can be considered as "message packets" and the range or data types can be checked, for data generated from one unit, and tested for validity before being passed into another unit. One option for interface testing is to keep a separate log file of data items being passed, often with a timestamp logged to allow analysis of thousands of cases of data passed between units for days or weeks. Tests can include checking the handling of some extreme data values while other interface variables are passed as normal values.[34] Unusual data values in an interface can help explain unexpected performance in the next unit. Component interface testing is a variation of black-box testing, [35] with the focus on the data values beyond just the related actions of a subsystem component. System testing[edit] Main article: System testing System testing, or end-to-end testing, tests a completely integrated system to verify that the system meets its requirements.[36] For example, a system test might involve testing a logon interface, then creating and editing an entry, plus sending or printing results, followed by summary processing or deletion (or archiving) of entries, then logoff. Operational Acceptance testing[edit] Main article: Operational acceptance testing Operational Acceptance is used to conduct operational readiness (pre-release) of a product, service or system as part of a quality management system. OAT is a common type of non- functional software testing, used mainly in software development and software maintenance projects. This type of testing focuses on the operational readiness of the system to be supported, and/or to become part of the production environment. Hence, it is also known as operational readiness testing (ORT) or Operations readiness and assurance (OR&A) testing. Functional testing within OAT is limited to those tests which are required to verify the non-functional aspects of the system.
  26. 26. In addition, the software testing should ensure that the portability of the system, as well as working as expected, does not also damage or partially corrupt its operating environment or cause other processes within that environment to become inoperative.[37] Bugzilla. Bugzilla is a Web-based general-purpose bugtracker and testing tool originally developed and used by the Mozilla project, and licensed under the Mozilla Public License. Released as open source software by Netscape Communications in 1998, it has been adopted by a variety of organizations for use as a bug tracking system for both free and open source software and proprietary projects and products. Bugzilla is used, among others, by Mozilla Foundation, Wikimedia Foundation, WebKit, NASA, Yahoo!, GNOME, KDE, Red Hat and Novell.[2] Documentation Developing good user documentation is an important part of the implementation process. Sample data entry display screens, forms, and reports are good examples of documentation. When computer-aided systems engineering methods are used, documentation can be created and changed easily since it is stored and accessible on disk in a system repository. Documentation serves as a method of communication among the people responsible for developing, implementing, and maintaining a computer-based system. Installing and operating a newly designed system or modifying an established application requires a detailed record of that system’s design. Documentation is extremely important in diagnosing errors and making changes, especially if the end users or systems analyst who developed a system are no longer with the organization. Training Training is a vital implementation activity. IS personnel, such as user consultants, must be sure that end users are trained to operate a new e-business system or its implementation will fail. Training may involve only activities like data entry, or it may
  27. 27. also involve all aspects of the proper use of a new system. In addition, managers and end users must be educated in how the new technology impacts the company’s business operations and management. This knowledge should be supplemented by training programs for any new hardware devices, software packages, and their use for specific work activities. - Seminars o General - On the job training o Specific Conversion methods The initial operation of a new business system can be a difficult task. This typically requires a conversion process from the use of a present system to the operation of a new or improved application. Conversion methods can soften the impact of introducing new information technologies into an organization. Four major forms of system conversion are illustrated in figure. Figure: Conversion methods. Old System New System Old System New System Old System New System Parallel Pilot Phased
  28. 28. Old System New System Conversions can be • Parallel • Phased • Pilot • Plunge or direct cutover Conversions can be done on a parallel basis, whereby both the old and the new systems are operating until the project development team and end user management agree to switch completely over to the new system. It is during this time that the operations and results of both systems are compared and evaluated. Errors can be identified and corrected, and the operating problems can be solved before the old system is abandoned. Installation can also be accomplished by a direct cutover or plunge to a newly developed system. Conversion can also be done on a phased basis, where only parts of a new application or only a few departments, branch offices, or plant locations at a time are converted. A phased conversion allows a gradual implementation process to take place within an organization. Similar benefits accrue from using a pilot conversion, were one department or other work site serves as a test site. A new system can be tried out at this site until developers feel it can be implemented through out the organization. IS maintenance Once a system is fully implemented and is being used in business operations, the maintenance function begins. System maintenance is the monitoring, evaluating, and modifying of operational business systems to make desirable or necessary improvements. For example, the implementation of a new system usually results in the phenomenon known as the learning curve. Personnel who operate and use the system will make mistakes simply because they are not familiar with it. Though such Plunge (direct)
  29. 29. errors usually diminish as experience is gained with a new system, they do point out areas where a system may be improved. Maintenance is also necessary for other failures and problems that arise during the operation of a system. End users and information systems personnel then perform a troubleshooting function to determine the causes of and solutions to such problems. The maintenance activity includes a post-implementation review process to ensure that newly implemented systems meet the business objectives established for them. Errors in the development or use of a system must be corrected by the maintenance process. This includes a periodic review or audit of a system to ensure that it is operating properly and meeting its objectives. This audit is in addition to continually monitoring a new system for potential problems or necessary changes. Maintenance also includes making modifications to an established system due to changes in the business organization or the business environment. For example, new tax legislation, company reorganizations, and new e-commerce initiatives may require major changes to current business system. E-learning; ITU Hospital Management Certificate Program http://www.enoctaakademi.com Online analytical processing From Wikipedia, the free encyclopedia (Redirected from OLAP) In computing, online analytical processing, or OLAP (pronounced /ˈoʊlæp/) is an approach to swiftly answer multi- dimensional analytical queries.[1] OLAP is part of the broader category of business intelligence, which also encompasses relational reporting and data mining.[2] Typical applications of OLAP include business reporting for sales, marketing,management reporting, business process management (BPM)[3] , budgeting and forecasting, financial reporting and similar areas, with new applications coming up, such as agriculture [4] . The term OLAP was created as a slight modification of the traditional database term OLTP (Online Transaction Processing).[5] Databases configured for OLAP use a multidimensional data model, allowing for complex analytical and ad-hoc queries with a rapid execution time. They borrow aspects of navigational databases and hierarchical databases that are faster than relational databases.[6]
  30. 30. The output of an OLAP query is typically displayed in a matrix (or pivot) format. The dimensions form the rows and columns of the matrix; the measures form the values. Data warehouse From Wikipedia, the free encyclopedia Data Warehouse Overview In computing, a data warehouse or enterprise data warehouse (DW, DWH, or EDW) is a database used for reporting and data analysis. It is a central repository of data which is created by integrating data from multiple disparate sources. Data warehouses store current as well as historical data and are used for creating trending reports for senior management reporting such as annual and quarterly comparisons. The data stored in the warehouse are uploaded from the operational systems (such as marketing, sales etc., shown in the figure to the right). The data may pass through an operational data store for additional operations before they are used in the DW for reporting. The typical ETL-based data warehouse uses staging, integration, and access layers to house its key functions. The staging layer or staging database stores raw data extracted from each of the disparate source data systems. The integration layer integrates the disparate data sets by transforming the data from the staging layer often storing this transformed data in an operational data store (ODS) database. The integrated data are then moved to yet another database, often called the data warehouse database, where the data is arranged into hierarchical groups often called dimensions and into facts and aggregate facts. The combination of facts and dimensions is sometimes called a star schema. The access layer helps users retrieve data.[1] A data warehouse constructed from an integrated data source systems does not require ETL, staging databases, or operational data store databases. The integrated data source systems may be considered to be a part of a distributed operational data store layer. Data federation methods or data virtualization methods may be used to access the distributed integrated source data systems to consolidate and aggregate data directly into the data warehouse database tables. Unlike the ETL-based data
  31. 31. warehouse, the integrated source data systems and the data warehouse are all integrated since there is no transformation of dimensional or reference data. This integrated data warehouse architecture supports the drill down from the aggregate data of the data warehouse to the transactional data of the integrated source data systems. Data warehouses can be subdivided into data marts. Data marts store subsets of data from a warehouse. This definition of the data warehouse focuses on data storage. The main source of the data is cleaned, transformed, cataloged and made available for use by managers and other business professionals for data mining, online analytical processing, market research and decision support (Marakas & O'Brien 2009). However, the means to retrieve and analyze data, to extract, transform and load data, and to manage the data dictionary are also considered essential components of a data warehousing system. Many references to data warehousing use this broader context. Thus, an expanded definition for data warehousing includes business intelligence tools, tools to extract, transform and load data into the repository, and tools to manage and retrieve metadata. Data mart From Wikipedia, the free encyclopedia A data mart is the access layer of the data warehouse environment that is used to get data out to the users. The data mart is a subset of the data warehouse that is usually oriented to a specific business line or team. In some deployments, each department or business unit is considered the owner of its data mart including all the hardware, software and data.[1] This enables each department to use, manipulate and develop their data any way they see fit; without altering information inside other data marts or the data warehouse. In other deployments where conformed dimensions are used, this business unit ownership will not hold true for shared dimensions like customer, product, etc. The related term spreadmart describes the situation that occurs when one or more business analysts develop a system of linked spreadsheets to perform a business analysis, then grow it to a size and degree of complexity that makes it nearly impossible to maintain. The primary use for a data mart is business intelligence (BI) applications. BI is used to gather, store, access and analyze data. The data mart can be used by smaller businesses to utilize the data they have accumulated. A data mart can be less expensive than implementing a data warehouse, thus making it more cost effective for the small business. A data mart can also be set up in much less time than a data warehouse, being able to be set up in less than 90 days. Since most small businesses only have use for a small number of BI applications, the low cost and quick set up of the data mart makes it a suitable method for storing data.[2]
  32. 32. Big data From Wikipedia, the free encyclopedia A visualization created by IBM of Wikipedia edits. At multiple terabytes in size, the text and images of Wikipedia are a classic example of big data. In information technology, big data[1][2] is a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools. The challenges include capture, curation, storage,[3] search, sharing, analysis,[4] and visualization. The trend to larger data sets is due to the additional information derivable from analysis of a single large set of related data, as compared to separate smaller sets with the same total amount of data, allowing correlations to be found to "spot business trends, determine quality of research, prevent diseases, link legal citations, combat crime, and determine real-time roadway traffic conditions."[5][6][7] As of 2012, limits on the size of data sets that are feasible to process in a reasonable amount of time were on the order of exabytes of data.[8][9] Scientists regularly encounter limitations due to large data sets in many areas, including meteorology, genomics,[10] connectomics, complex physics simulations,[11] and biological and environmental research.[12] The limitations also affect Internet search, finance andbusiness informatics. Data sets grow in size in part because they are increasingly being gathered by ubiquitous information- sensing mobile devices, aerial sensory technologies (remote sensing), software logs, cameras, microphones, radio-frequency identification readers, and wireless sensor networks.[13][14] The world's technological per-capita capacity to store information has roughly doubled every 40 months since the 1980s;[15] as of 2012, every day 2.5 quintillion (2.5×1018 ) bytes of data were created.[16] Big data is difficult to work with using relational databases and desktop statistics and visualization packages, requiring instead "massively parallel software running on tens, hundreds, or even thousands of servers".[17] What is considered "big data" varies depending on the capabilities of the organization managing the set. "For some organizations, facing hundreds of gigabytes of data for the first time may trigger a need
  33. 33. to reconsider data management options. For others, it may take tens or hundreds of terabytes before data size becomes a significant consideration."[18] Agile software development From Wikipedia, the free encyclopedia Agile software development poster Generic diagram of an agile methodology for software development Agile software development is a group of software development methods based on iterative and incremental development, where requirements and solutions evolve through collaboration between self- organizing, cross-functional teams. It promotes adaptive planning, evolutionary development and delivery, a time-boxed iterative approach, and encourages rapid and flexible response to change. It is a conceptual framework that promotes foreseen interactions throughout the development cycle. The Agile Manifesto[1] introduced the term in 2001.
  34. 34. BALANCED SCORECARD AI: ARTIFICIAL INTELLIGENCE http://easydiagnosis.com/ expert system Recommender system From Wikipedia, the free encyclopedia (Redirected from Recommendation systems) Recommender systems or recommendation systems (sometimes replacing "system" with a synonym such as platform or engine) are a subclass of information filtering system that seek to predict the 'rating' or 'preference' that user would give to an item (such as music, books, or movies) or social element (e.g. people or groups) they had not yet considered, using a model built from the characteristics of an item (content-based approaches) or the user's social environment (collaborative filtering approaches).[1][2] Recommender systems have become extremely common in recent years. A few examples of such systems: • When viewing a product on Amazon.com, the store will recommend additional items based on a matrix of what other shoppers bought along with the currently selected item.[3] • Pandora Radio takes an initial input of a song or musician and plays music with similar characteristics (based on a series of keywords attributed to the inputted artist or piece of music). The stations created by Pandora can be refined through user feedback (emphasizing or deemphasizing certain characteristics). • Netflix offers predictions of movies that a user might like to watch based on the user's previous ratings and watching habits (as compared to the behavior of other users), also taking into account the characteristics (such as the genre) of the film. http://p1m1.com/solutions/ DECISION SUPPORT SYSTEMS SAS is a software suite developed by SAS Institute for advanced analytics, business intelligence, data management, and predictive analytics. Statistical analysis Software http://ecommerce-software-review.toptenreviews.com/
  35. 35. 2015: https://www.facebook.com/BigThinkdotcom/videos/1015408123301852/

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