INFORMATION SYSTEM

INFORMATION SYSTEM OLD QUESTION SOLUTION,IOE , 2077-CHAITRA

 

1.  What is an Information System? What are the differences between IT and IS? Write at least four types of IS, with brief explanations of each type.

An Information System is a combination of people, processes, hardware, software, and data that work together to collect, process, store, and disseminate information needed to support an organization's operations, management, and decision-making activities. It can be used for a variety of purposes, such as improving efficiency, reducing costs, enhancing communication, and providing a competitive advantage.

The types of IS are:

 

1. Transaction Processing Systems (TPS): These are systems that support the collection, processing, and storage of transaction data, such as sales orders, invoices, and payments. They are typically used by operational staff to perform day-to-day tasks and generate reports.
2. Management Information Systems (MIS): These are systems that provide middle managers with the information they need to monitor and control the organization's activities. They typically provide summary reports and analysis of data collected from various sources.
3. Decision Support Systems (DSS): These are systems that provide managers and executives with the tools and information they need to make strategic decisions. They typically use analytical models and data from various sources to support decision-making.
4. Expert Systems (ES): ES is an information system that emulates the decision-making ability of a human expert. It uses artificial intelligence to analyze data and provide recommendations based on its knowledge base.

The difference between IT and IS is given below:

 

 

 

 

 

 

 

2.   Mention any three levels of securities that could be implemented while building any IS with brief explanation. Is ‘Security Policy’ the same as ‘Security Method’? Justify your argument with appropriate example of IS implementation scenario

Three levels of security that could be implemented while building an IS are:

 

1. Physical Security: This level of security is concerned with protecting the physical infrastructure of the IS, such as buildings, equipment, and data centers. Physical security measures include access controls, surveillance systems, and environmental controls such as fire suppression and temperature control systems.
2. Network Security: This level of security is concerned with protecting the network infrastructure of the IS, such as routers, switches, and servers. Network security measures include firewalls, intrusion detection and prevention systems, and encryption technologies.
3. Information Security: This level of security is concerned with protecting the data and information that is stored and processed by the IS. Information security measures include access controls, authentication and authorization systems, and data encryption.

Security Policy and Security Method are not the same things. A Security Policy is a set of rules and guidelines that define how an organization will protect its information assets, while a Security Method is a specific approach or technique used to implement those rules and guidelines.

For example, consider an organization that wants to implement a Security Policy to protect its customer data. The Security Policy might require that all employees use strong passwords and two-factor authentication to access the customer data. The Security Method used to implement this policy might be to use a password management system that enforces strong passwords and requires two-factor authentication.

In this scenario, the Security Policy defines what needs to be done to protect the customer data, while the Security Method defines how it will be done.

 

3.   What is the hierarchical relationship among data, information and knowledge (DIK)? Establish DIK linkages associating with domain and system knowledge. Illustrate all in a single diagram.

Data, information, and knowledge (DIK) are related to each other in a hierarchical manner, with each concept building on the previous one. Data is the raw material that represents facts, figures, and symbols without any context or meaning. It can be in the form of numbers, words, or images. Information is derived from data by organizing, interpreting, and adding context to it. It provides a framework for understanding the data and making sense of it. Information can be thought of as organized data that has meaning and value. Knowledge is derived from information by adding experience, expertise, and in-sights to it. It is a more comprehensive and deep understanding of a subject matter. Knowledge allows us to apply information in new and unique ways, solve problems, and make decisions. The relationship between DIK can be illustrated using the following diagram:

Data –> Information –> Knowledge

 

In terms of domain knowledge, domain-specific data provides the basis for domain- specific information, which in turn leads to domain-specific knowledge. For example, in the field of medicine, patient data can be used to generate medical information that can be used to develop medical knowledge. Similarly, in the field of finance, financial data can be used to generate financial information, which can be used to develop financial knowledge. In terms of system knowledge, data generated by a system can be used to generate system-specific information, which can be used to develop system-specific knowledge. For example, data generated by a manufacturing process can be used to generate information about the process, which can be used to develop knowledge about how to optimize and improve the process. Similarly, data generated by a computer network can be used to generate information about the network, which can be used to develop knowledge about how to troubleshoot and maintain the network.

4.  Why change management is required? What are the key principles of change management? Write briefly within the IS context.

 

Change management is required in order to successfully implement changes to an organization's Information System (IS). This is because changes to an IS can affect the organization's processes, people, and technology, and can lead to resistance, confusion, and errors if not managed properly. Change management is the process of planning, implementing, and monitoring changes to an IS in a structured and controlled manner.

The key principles of change management within an IS context are:

 

1. Clearly define the scope and objectives of the change: It is important to define the scope and objectives of the change, including the expected benefits and risks, in order to ensure that the change is aligned with the organization's overall goals.
2. Develop a detailed plan: A detailed plan should be developed that outlines the activities, timeline, and resources needed to implement the change. The plan should also identify the roles and responsibilities of the various stakeholders involved in the change.
3. Communicate effectively: Effective communication is critical to the success of a change management initiative. The communication plan should be developed that provides clear and timely information about the change to all stakeholders.
4. Identify and manage risks: Risks associated with the change should be identified and managed throughout the change management process. This includes assessing the impact of the change on the organization's processes, people, and technology, and developing mitigation strategies to address any potential issues.
5. Engage stakeholders: It is important to engage all stakeholders, including employees, customers, and partners, throughout the change management process. This includes involving them in the planning and implementation of the change, and addressing their concerns and feedback.
6. Monitor and evaluate: The change management process should be monitored and evaluated to ensure that it is achieving the desired outcomes. This includes measuring the effectiveness of the change, identifying areas for improvement, and making adjustments as needed.

 

 

 

 

5.   What is a recommender system? How does a collaborative filtering method generate potential recommendations? Explain in brief with sample example

A recommender system is a type of information filtering system that provides suggestions for items that are most relevant to a particular user1. Recommender systems are widely used in e-commerce, streaming services, social media, and other domains to help users find products or content that match their preferences or needs.

 

One of the common methods for generating recommendations is collaborative filtering, which uses the ratings or feedback of other users who have similar tastes or interests as the target user. 

Collaborative filtering can be divided into two main types: user-based and item-based. 

 

User-based collaborative filtering finds other users who have rated items similarly to the target user, and recommends items that those users liked. 

 

Item-based collaborative filtering finds items that have been rated similarly by other users, and recommends items that are similar to what the target user liked.

 

For example, suppose Alice is a movie lover who has rated some movies on a streaming service. User-based collaborative filtering would look for other users who have rated movies similarly to Alice, such as Bob and Carol. Then it would recommend movies that Bob and Carol liked but Alice has not seen yet, such as The Matrix or The Godfather. 

Item-based collaborative filtering would look for movies that have been rated similarly by other users, such as Titanic and The Notebook. Then it would recommend movies that are similar to what Alice liked, such as A Star Is Born or The Fault in Our Stars.

6.   Define cloud computing. Why is cloud computing knowledge becoming an essential for any seasoned IS designing professional? Justify.

Cloud computing is the practice of using a network of remote servers hosted on the internet to store, manage, and process data, rather than a local server or a personal computer1. Cloud computing offers various benefits such as faster innovation, flexible resources, and economies of scale2. Users can access cloud services on demand and pay only for what they use.

 

Cloud computing knowledge is becoming essential for any seasoned IS designing professional because cloud computing is transforming how information systems are developed, deployed, and maintained. Cloud computing enables IS designers to leverage existing cloud platforms and services that offer high performance, scalability, reliability, security, and cost-effectiveness. Cloud computing also allows IS designers to create innovative solutions that can meet the changing needs and expectations of users and stakeholders. Cloud computing also poses new challenges and opportunities for IS designers such as data privacy, governance, integration, migration, interoperability, etc.

 

Therefore, cloud computing knowledge is crucial for any IS designing professional who wants to stay updated with the latest trends and technologies in the field of information systems.

 

7.   What is CRM? How closely is CRM associated with SCM? Why is SCM and CRM becoming important in e-commerce in comparison to regular brick-and-mortar commerce? 

 

CRM stands for customer relationship management, which is a technology for managing all your company’s relationships and interactions with customers and potential customers. 

CRM helps companies stay connected to customers, streamline processes, and improve profitability

SCM stands for supply chain management, which is the management of the flow of goods and services from raw materials to final products. SCM involves planning, coordinating, and controlling the activities of suppliers, manufacturers, distributors, retailers, and customers.

 

CRM and SCM are closely associated because they both aim to optimize customer satisfaction and business performance. CRM focuses on the demand side of the market, while SCM focuses on the supply side. CRM helps companies understand customer needs and preferences, while SCM helps companies deliver products and services efficiently and effectively. CRM and SCM can work together to create a seamless customer experience across the entire value chain.

 

CRM and SCM are becoming more important in e-commerce than in regular brick-and-mortar commerce because e-commerce involves more complex and dynamic interactions between customers and suppliers. E-commerce customers have higher expectations for personalization, convenience, speed, quality, and service than traditional customers. E-commerce suppliers have to deal with more competition, uncertainty, variability, and risk than traditional suppliers. Therefore, e-commerce requires more sophisticated CRM and SCM systems that can handle large volumes of data, support multiple channels of communication, enable real-time decision making, and facilitate collaboration among different parties.

8. Compare and contrast the following:

a)  Fully integrated vs Loosely integrated enterprises

 

b)  CSF vs KPI

 

 

c)  Web content mining vs Web uses mining

 

d)  MapReduce vs Hadoop System

 

9.Write short notes on the followings:

a)  ERP System in large organization

 

Enterprise Resource Planning system is a software suite that integrates and manages all the core business processes and data of an organization, including finance, human resources, supply chain management, manufacturing, customer relationship management, and more. ERP systems are

 

designed to provide a unified view of an organization's operations, with real-time visibility into key performance indicators and metrics.

ERP systems are particularly valuable for large organizations that have complex and diverse business processes, multiple locations, and large volumes of data. By using an ERP system, large organizations can streamline their operations, eliminate data silos, improve communication and collaboration across departments and teams, and make better-informed decisions.

However, implementing an ERP system in a large organization can be complex and challenging. It requires careful planning, coordination, and communication among all the stakeholders, as well as a significant investment in resources and training. Nonetheless, the potential benefits of an ERP system for large organizations can make the effort and cost worthwhile.

 

b)  CIA Triangle

 

The CIA triangle is a well-known model in information security that consists of three fundamental elements: confidentiality, integrity, and availability. These three elements are often referred to as the CIA triad and form the basis of information security planning, implementation, and evaluation.

1.     Confidentiality: Confidentiality refers to the protection of sensitive information from unauthorized access, disclosure, or use. Confidentiality is achieved through access controls, encryption, and other security measures that restrict access to information only to authorized individuals or systems.

2.     Integrity: Integrity refers to the accuracy, completeness, and consistency of information over its entire life cycle. Integrity is achieved through controls that prevent unauthorized modification, deletion, or destruction of information, and ensure that information is not altered or corrupted during transmission or processing.

3.     Availability: Availability refers to the accessibility and usability of information and systems by authorized users when needed. Availability is achieved through measures that prevent or mitigate system failures, outages, or other disruptions that could prevent users from accessing or using information or systems.

The CIA triangle is a useful tool for identifying and prioritizing security risks and for designing and implementing appropriate security controls. Effective security measures must balance the three elements of the CIA triangle to ensure that sensitive information is protected while remaining accessible and usable by authorized users.

 

c)  Collective intelligence through social network

 

Collective intelligence refers to the ability of a group of individuals to solve complex problems, make decisions, or generate new ideas through collaboration and knowledge sharing. Social networks, such as Facebook, Twitter, and LinkedIn, can facilitate collective intelligence by connecting people with similar interests and expertise, enabling them to exchange information, opinions, and feedback.

Through social networks, individuals can participate in various forms of collective intelligence, such as crowdsourcing, collaborative filtering, and social computing. Crowdsourcing involves engaging a large group of people to perform a task or solve a problem, such as funding a project or identifying a new product feature. Collaborative filtering involves using the collective opinions and preferences of a group of users to make recommendations or predictions, such as in product or content recommendations. Social computing involves using social media and other web-based tools to collaborate, share knowledge, and solve problems.

Social networks also offer opportunities for individuals to form communities of practice, where they can share expertise, learn from each other, and collaborate on projects or initiatives. These communities can be particularly valuable in fields such as science, technology, and innovation, where complex problems require interdisciplinary and collaborative approaches.

 

d)  Big-Data processing with MapReduce

 

MapReduce is a programming model and software framework used for processing large data sets in a distributed computing environment. It was developed by Google to handle massive data processing in a scalable and efficient way. MapReduce enables the processing of big data by breaking it down into smaller, manageable parts and distributing the processing of these parts across multiple machines in a cluster.

The MapReduce framework consists of two main functions: Map and Reduce. The Map function takes input data and transforms it into key-value pairs, which are then passed to the Reduce function. The Reduce function takes the output of the Map function and performs a summarization or aggregation operation on the data, producing a final output.

The key benefits of MapReduce for big-data processing include its ability to handle large volumes of data, its scalability, fault-tolerance, and its ability to handle unstructured and semi-structured data. MapReduce can be used for a wide range of big-data processing tasks, including data cleaning and preprocessing, data mining and analysis, machine learning, and natural language processing.