Assignment Code: MMPC-008 / TMA / JAN / 2023

Course Code: MMPC-008

Assignment Name: Information Systems for Managers

Year: 2023

Verification Status: Verified by Professor

Note: Attempt all the questions.

Q 1. “Information Technology (IT) has become a strategic necessity.” What do you understand by the term information technology? Also, explain the various types of information systems.

Ans) As technology continues to advance, businesses and organizations are increasingly relying on Information Technology to drive their operations, improve their efficiency, and gain a competitive advantage. IT has become a strategic necessity for many organizations, and without it, they may struggle to keep up with their competitors. One of the key benefits of IT is its ability to enable automation and streamline processes, which can help businesses to operate more efficiently and reduce costs. IT can also provide valuable insights through data analytics, helping businesses to make informed decisions and optimize their operations. Moreover, IT has transformed the way companies interact with their customers, making it easier to communicate with them, understand their needs, and personalize their experiences. IT has also revolutionized marketing and sales, providing new channels and tools to reach potential customers and increase sales.

In today's digital age, businesses that fail to embrace and leverage technology are likely to fall behind their competitors. Therefore, IT has become an essential part of business strategy, and companies must invest in it to stay competitive and relevant in their respective industries.

Information Technology (IT) refers to the use of computers, software, hardware, and other technologies to manage, store, process, and transmit data and information. IT encompasses a wide range of activities related to computing and telecommunications, including designing and developing software applications, managing networks and databases, creating and maintaining websites, and providing technical support. IT plays a critical role in many aspects of modern society, from business and healthcare to education and entertainment. IT has also transformed the way people communicate, access information, and conduct transactions, and it continues to drive innovation and change in many industries.

Some of the key areas of IT include:

1. Computer hardware: This includes the physical components of a computer system, such as the central processing unit (CPU), memory, hard drive, and input/output devices.

2. Software: This refers to computer programs that perform specific tasks, such as operating systems, productivity software, and specialized applications.

3. Networking: This involves connecting computers and devices together to share data and resources, such as printers and servers.

4. Internet and Web technologies: These technologies enable people to access and share information over the internet, including websites, email, social media, and e-commerce platforms.

5. Cybersecurity: This involves protecting computer systems and networks from unauthorized access, theft, and damage, through the use of security software, encryption, and other measures.

There are several types of information systems that are used in organizations to manage and process data and information. These systems can be classified based on their purpose, functionality, and level of support they provide to organizational activities.

Some of the most common types of information systems are:

1. Transaction Processing Systems (TPS): TPS are used to process and record transactions such as sales, payments, and purchases. These systems ensure that transactional data is accurate and processed in a timely manner.

2. Management Information Systems (MIS): MIS provide managers with information needed to make decisions, such as financial and performance data. These systems are used to monitor operations and support tactical decision-making.

3. Decision Support Systems (DSS): DSS are used to support decision-making in a specific area or situation. They help managers to analyze data and evaluate alternatives.

4. Executive Information Systems (EIS): EIS are designed to provide high-level executives with quick access to key performance indicators (KPIs) and other critical information needed to make strategic decisions.

5. Knowledge Management Systems (KMS): KMS are used to capture, store, and share knowledge and expertise within an organization. These systems enable employees to access and share information, best practices, and lessons learned.

6. Enterprise Resource Planning (ERP) Systems: ERP systems integrate all aspects of a business, including finance, accounting, human resources, and supply chain management, into a single system. They provide a unified view of an organization's operations and facilitate information sharing across different departments.

7. Expert Systems: The system has the ability to make suggestions and act like an expert in a

   particular field. An expert system has an extensive knowledge base. Nowadays such systems are in use for automating business processes to great extent. It is envisaged that expert systems will be in high demand further in future.

8. Workflow system: A workflow system is a rule-based management system that guides, coordinates, and keeps an eye on the execution of a business process, which is a set of related tasks. A document image management system is another name for a workflow system. For example, banks use a workflow system for the loan approval process. On a bank's website, a person who wants a loan fills out an electronic application form. After that, the application is sent to the site of the bank loan officer. The loan officer talks to the person applying for the loan, writes down his thoughts, and sends the application to the credit check unit. The credit unit fills in the details and checks the credit limit. Now that the application is done, a decision has been made.

These are just a few examples of the different kinds of information systems that organisations use today. Each system has a different goal and set of features, but they all work together to help organisations run their businesses, make good decisions, and stay competitive in their fields.

Q 2. “Cloud architecture has emerged as technology components that are combined to build a cloud.” Comment on the statement.

Ans) The statement "Cloud architecture has emerged as technology components that are combined to build a cloud" is accurate. Cloud architecture refers to the design and organization of the various components and technologies that make up a cloud computing system. These components include servers, storage devices, networking infrastructure, software applications, and other resources that are used to create and deliver cloud services.

Cloud architecture is typically based on a set of core principles, such as scalability, reliability, flexibility, and security. These principles are used to guide the design and implementation of the various components that make up a cloud, in order to ensure that the system can meet the needs of its users and deliver high-quality services.

The design of cloud architecture involves the selection and integration of various technology components that are combined to create a cloud infrastructure. These components may include virtualization technologies, such as hypervisors and containers, storage systems, such as storage area networks (SANs) and network-attached storage (NAS), and networking technologies, such as switches and routers.

In addition, cloud architecture may also involve the use of specialized software platforms and applications that are designed to support specific cloud services, such as database management systems, big data analytics tools, and software development platforms.

Cloud architecture is an important consideration for any organization that is planning to adopt cloud computing technologies, as it can have a significant impact on the performance, reliability, and security of the cloud environment. By designing a well-architected cloud infrastructure, organizations can ensure that their cloud services are scalable, flexible, and secure, and can deliver the performance and reliability that their users require.

The components of cloud architecture include:

1. A front-end platform (the client or device used to access the cloud).

2. One or more back-end platforms (servers and storage).

3. A cloud-based delivery methodology.

4. A network to connect cloud clients, servers, and storage.

Together, these technologies create a cloud computing architecture on which applications can run, providing end-users with the ability to leverage the power of cloud resources. The concept of cloud computing is, however, remarkably similar to mainframe computing, popular since the 1960s, where centralized servers ran applications that were accessed by ‘dumb’ terminals connected to a private network. Cloud computing architecture enables organizations to reduce or eliminate their reliance on on-premises server, storage, and networking infrastructure. Organizations adopting cloud architecture often shift IT resources to the public cloud, eliminating the need for on-premises servers and storage. This reduces overhead cost and the need for IT data Center, cooling, and power requirements. Instead, the overhead cost is replaced them with a monthly IT expenditure. With mutual agreement the payment terms may be even Networking Technologies quarterly, half-yearly or annually.

This change from capital costs to operating costs is a big reason why cloud computing is so popular right now. There are three main types of cloud architecture that are pushing organisations to use the cloud. Each of these has its own key features and benefits.

1) Software as a Service (SaaS): Software and applications are delivered and kept up to date by SaaS architecture providers over the Internet. So, it gets rid of the need to put the software in place locally. Most SaaS apps are accessed through a web interface. ERP, SAP, CRM, SCM, PMS, and other software solutions, such as those for hospital and patient management, virtual meetings, and online training programmes, can be done for less money.

2) Platform as a Service (PaaS): In this cloud model, the service provider offers as a service a computing platform and solution stack, which usually includes middleware. Organizations can build an application or service on top of that platform. The cloud service provider gives an application the networks, servers, and storage space it needs to run, while the end user is in charge of installing software and setting up its settings.

3) Infrastructure as a Service (IaaS): This kind of cloud architecture is the simplest. In this way, a third-party provider takes care of the infrastructure, so organisations don't have to buy servers, networks, or storage devices. On the other hand, organisations manage their own software and applications and only pay for the servers and storage space they need at any given time.

In conclusion, cloud architecture is a very useful tool for businesses that want to improve their IT infrastructure, cut costs, and become more agile and flexible. By using the key parts of cloud architecture, organisations can build and run scalable, reliable, and secure cloud-based systems that can help them move forward in their digital transformation efforts. Cloud architecture is a key part of any cloud computing system. It involves choosing and putting together different pieces of technology to make a scalable, reliable, flexible, and secure cloud infrastructure. The architecture of the cloud is important to the success of cloud computing because it can affect how fast, reliable, and safe the cloud environment is. So, cloud architecture should be thought about carefully when planning and putting cloud computing solutions into place.

Q 3. Define the terms Management Information System(MIS), Decision Support System(DSS), and Executive Information System (EIS). State the difference between them.

Ans) Management Information System (MIS), Decision Support System (DSS), and Executive Information System (EIS) are all types of information systems used in organizations to support decision-making processes. Although they share some similarities, they have distinct differences in terms of their purpose, scope, and functionality.

Management Information System (MIS)

The acronym "MIS" stands for "management information system," and it refers to a type of information system that gives managers the data they require to make intelligent decisions. Data from various sources within a company, such as transaction processing systems, operational databases, and external sources, are often included in MIS. The management information system (MIS) generates reports and dashboards that summarise and analyse this data. This enables managers to monitor and oversee organisational performance, detect problems and opportunities, and make choices based on accurate information.

The management information system (MIS) gives managers access to information about the past and current performance of the company, such as sales, inventory levels, production output, and financial results. This information is often given in an organised manner, such as tables, charts, and graphs. The most common application of management information systems (MIS) is in the making of operational decisions, such as determining inventory levels, scheduling production, and allocating resources.

Decision Support System (DSS)

A decision support system, often known as a DSS, is an information system that helps in the process of making decisions by providing analytical tools and models that can be used to analyse and evaluate data. Data that is contained inside DSS often originates from a wide variety of sources, including as operational databases, external sources, and data warehouses. Users of the DSS are given access to interactive tools and models that allow them to perform data analysis, investigate a variety of potential outcomes, and weigh their options.

Decision support systems (DSS) are utilised to provide assistance with decision-making procedures that deal with complicated, unstructured, and strategic challenges. DSS gives managers insights into both the internal and external environments of the firm. With this information, managers are able to make more informed decisions regarding issues such as product development, market entry, and strategic planning. The decision-making tools that are commonly included in DSS include the "what-if" analysis, the sensitivity analysis, and the simulation models.

Executive Information System (EIS)

The Executive Information System, often known as EIS, is an information system that offers top executives a picture of the organization's performance that is both comprehensive and individualised to their specific needs. Data that is included in EIS often comes from a wide variety of sources, including as operational databases, external sources, and data warehouses. Dashboards and other visual tools are provided to senior executives by EIS. These tools summarise and analyse the data, enabling senior executives to monitor and control organisational performance as well as make strategic decisions based on accurate information.

EIS is utilised in the process of strategic decision-making, which includes activities such as the establishment of organisational goals, the creation of strategic plans, and the allocation of resources. EIS gives top leaders information on the internal and external environment of the firm, such as data on market trends, the performance of competitors, and customer preferences. The Enterprise Information System often incorporates features such as real-time data updates, individualised dashboards, and advanced analytics.

Difference between MIS, DSS, and EIS

The main differences between MIS, DSS, and EIS are:

1. Scope: MIS focuses on operational decision-making, DSS focuses on tactical decision-making, and EIS focuses on strategic decision-making.

2. Data: MIS primarily uses internal data, DSS uses both internal and external data, and EIS uses a combination of internal and external data.

3. Functionality: MIS focuses on reporting and monitoring, DSS focuses on analysis and evaluation, and EIS focuses on visualization and exploration.

4. User base: MIS is used by managers at all levels of the organization, DSS is used by middle managers and analysts, and EIS is used by senior executives.

In a nutshell, management information systems (MIS), decision support systems (DSS), and enterprise information systems (EIS) are all different kinds of information systems that are utilised in businesses to assist in the making of decisions. There are notable distinctions between them in regard to the functions that they perform, the areas of responsibility that they cover, and the types of users that employ them at various organisational levels. In order to choose the information system that will best serve the unique requirements of a company, it is vital to have a solid understanding of these distinctions.

Q 4. “Java has become a popular and useful programming language.” Explain, in view of the statement, the features of Java.

Ans) Sun Microsystems released Java in 1995. It was supposed to be a simple, object-oriented, and portable language for developing software for multiple platforms. Java is one of the most popular programming languages for enterprise, web, mobile, and gaming development. The language's platform-neutrality stands out. It lets programmers Write Once Run Anywhere (WORA) by running compiled Java code on all Java-supported platforms without recompilation. Java is the first platform-independent programming language. Java programmes run on any machine. Java is used to generate apps for over a billion desktops and 3 billion mobile phones.

Java has become a popular and useful programming language because of its excellent features. The important feature of Java is as under:

1. Simple and Familiar

Java's simplicity and ease of use make it important. Its syntax resembles C and C++, except it lacks references and operator overloading. Java is tightly typed and checks for type problems at compile time. Java programmes are straightforward. It uses C and C++ but removes their downsides and complications. Computer language is usually compiled or interpreted. Java's two-stage mechanism combines these concepts. Java compilers generate byte code from source code. Java Virtual Machine (JVM) runs this portable bytecode because it is not machine instructions. JVM generates machine code that Java program-running machines can directly execute.

2. Object-Oriented, secure, and Robust

Java, an object-oriented language, enables encapsulation, inheritance, and polymorphism. Modular, extendable, and reusable code saves time and reduces errors in object-oriented programming. Java is truly object-oriented. Java is mostly objects. Classes and objects hold all code and data. Java programmes require the class. Java strongly follows the Object-Oriented Programming notion of encapsulation (OOP). Malicious actions and viruses make programming language security crucial. Java checks memory access and prevents viruses. A bytecode validator checks code segments for improper access right code. Java handles run-time faults, offers additional features, and has a solid memory management mechanism. It eliminates errors by compiling and running the code.

3. High Performance, Dynamic and Extensible

Java's intermediate bytecode boosts performance for an interpreted language. Java's "JIT – Just In Time compiler" compiles code just when it is called, boosting performance. Time and efficiency are saved. Java architecture decreases runtime overheads. Multithreading accelerates Java programming. Java Virtual Machine executes highly efficient Java compiler bytecodes faster. Java is dynamic and extensible, so you can subclass classes to add new methods and create new classes. Java dynamically links class libraries, methods, and objects. Its adaptability makes it lively.

4. Platform Independent, Portable, and Architectural Neutral

Java was designed with the goal of enabling developers to write code once and run it on any platform without having to rewrite it. This is achieved through several important features of the Java programming language, including platform independence, portability, and architectural neutrality.

Platform independence: One of the most important features of Java is its platform independence. This means that Java code can run on any platform that has a Java Virtual Machine (JVM) installed, regardless of the underlying hardware and operating system. This is because Java code is compiled into bytecode, which is then interpreted by the JVM at runtime. The JVM acts as a virtual processor that executes the bytecode in a platform-independent manner.

Portability: Java's platform independence also gives it portability. Portability refers to the ability to move software from one platform to another without having to modify the code. Because Java code is compiled into bytecode, it can be easily transported and executed on any platform with a compatible JVM. This makes it easy for developers to write code that can be deployed on a wide variety of systems.

Architectural neutrality: Java is also designed to be architecturally neutral, which means that it is not tied to any specific hardware architecture. This is because the JVM, which interprets the bytecode, is responsible for translating the platform-independent bytecode into machine code that can be executed by the underlying hardware. This makes it possible for Java programs to run on a wide variety of hardware architectures without modification.

5. Distributed, Multi-threaded and Interactive

Java is a robust and versatile programming language that offers a number of key features to developers. Three of the most important features are its ability to support distributed computing, its support for multi-threaded programming, and its ability to create interactive applications. Let's take a closer look at each of these features:

Distributed computing: Java was designed with distributed computing in mind. This means that it has built-in features that enable developers to create software that can run on multiple computers connected by a network. This is achieved through the use of Java Remote Method Invocation (RMI), which allows objects in one Java Virtual Machine (JVM) to invoke methods on objects running in a different JVM.

Multi-threaded programming: Java is also designed to support multi-threaded programming. This means that developers can create programs that can execute multiple threads of code simultaneously, which can improve performance and responsiveness. Java provides built-in support for creating and managing threads, making it easy for developers to write multi-threaded applications.

Interactive applications: Finally, Java is well-suited for creating interactive applications. This means that developers can create applications that allow users to interact with them in real-time. Java provides a number of features for creating graphical user interfaces (GUIs), including the Swing toolkit, which allows developers to create custom components and layouts for their applications.

In conclusion, Java is popular and helpful because to its simplicity, object-oriented features, platform independence, automatic memory management, vast standard library, security features, and fast performance. These capabilities make it a popular language for designing everything from desktop apps to enterprise systems. Java will undoubtedly remain a vital software development language as technology advances.

Q 5. “Artificial Intelligence (AI) has roots from the time when the computer became a commercial reality.” Explain, in view of the statement, the history of artificial intelligence.

Ans) Artificial Intelligence (AI) has a long and rich history that dates back to the early days of computing. The field of AI emerged in the mid-twentieth century when researchers began to explore the possibility of creating machines that could think and reason like humans.

Brief History of AI

1. Works before 50’s

AI can be traced all the way back to the 1940s and 1950s, when computers were first being made. At that time, scientists started to think about how they could make machines that could do tasks that required intelligence. When the Turing Machine was shown to be able to manipulate symbols as well as numbers, machine intelligence was born. Cybernetics, the study of how humans and machines communicate, became a field. New ways of thinking about language theories were developed. Computers became a commercial reality. Theories like information theory, Boolean algebra, switching theory, and statistical decision theory were created. At that time, scientists started to think about how they could make machines that could do tasks that required intelligence.

2. Works after 50’s

Programs that play chess, translate languages, prove theorems automatically, and create new programming languages are all things that are being worked on. FORTRAN, LISP, computational linguistics, pattern recognition, and natural language processing were all made. At the Dartmouth Conference, which took place in 1956, researchers from many different fields got together to talk about how to make machines that can think for themselves.

3. Works in the 60’s

Program to play checkers, resolution as an inference method in logic; first knowledge-based expert system (DENDRAL); development of a large interactive general-purpose programme that solves math problems and simulates complicated ways of thinking. In the 1960s and 1970s, researchers started to look into the idea of machine learning, which is a branch of AI that focuses on making systems that can learn and get better over time. Statistical algorithms are used by machine learning systems to look for patterns and make predictions based on data.

4. Works in mid 70’s to 80’s

Expert systems that diagnose and prescribe medicines, expert systems that deal with real-life problems, uncertainty modelling, non-monotonic and spatio-temporal reasoning, etc., are all examples of specialised programmes about narrow problem areas that can help solve more complex problems that are useful in real life. Programmers made expert systems that can make decisions like an expert would. In the 1980s and 1990s, AI research focused on making "expert systems," which were meant to help people make decisions by giving them advice and support. Expert systems used knowledge-based systems to store and retrieve information and reasoning algorithms to make decisions.

5. Works in 90’s

IBM Deep Blue beats world chess champion, Gary Kasparov, and became the first computer to beat a world chess champion.

6. Works in 1st decade of 21st Century

In the 2000s and after, AI research has focused on making deep learning systems, which are based on neural networks that can learn and get better over time. Deep learning systems have been used for a lot of different things, like recognising images, recognising speech, and processing natural language. AI came into the home for the first time in the form of a vacuum cleaner called Roomba. AI didn't start to be used in business until 2006. AI was also used by companies like Facebook, Twitter, and Netflix.

7. Works in 2nd decade of 21st Century

In 2011, IBM's Watson won the quiz show Jeopardy, where it had to answer difficult questions and solve riddles. Watson had shown that it could understand real language and quickly find answers to hard questions. In 2012, Google added a feature to its Android app called "Google Now" that could predict what the user would want to know. Eugene Goostman, a chatbot, did well on the "Turing test" and won a prize. In June 2012, Goostman won what was called the "largest-ever Turing test contest." It did this by convincing 29 percent of the judges that it was a real person. In November 2014, Amazon made Alexa, which is also just called Alexa. It is a technology that Amazon made for virtual assistants. It can be read in English, French, German, and Japanese. In the year 2018, IBM's "Project Debater" debated with two master debaters about difficult topics and also did very well. Google showed off an AI programme called "Duplex," which was a virtual assistant and took a hairdresser appointment over the phone. The woman on the other end of the line didn't realise she was talking to a machine.

AI has grown a lot in recent years, and one of the main reasons is that there are now a lot of data and powerful computers that can be used. With the help of big data analytics and cloud computing, it is now possible to process and analyse huge amounts of data in real time. This has given AI applications new ways to be used. AI has now reached an extremely high level. Deep learning, big data, and data science are all new ideas that are becoming very popular right now. AI is being used by companies like Google, Facebook, IBM, and Amazon to make amazing devices. The future of AI is exciting, and it will have a high level of intelligence.

In conclusion, artificial intelligence has been around since the beginning of computers, and it has changed over time as researchers have tried out new methods and technologies. AI has grown from early systems that could do simple tasks to modern deep learning systems that can learn and get better over time. It is now an important technology that is used in many different ways. As computer technology keeps getting better, it's likely that AI will get even smarter and more useful, giving us new ways to live and work.