INFORMATION SYSTEM

 

1. Identify and give examples of several major ways that enterprises are using the internet and intranet for business applications? List power of GIS and examples of powerful applications of GIS.

 

In today’s day and age, enterprises are using internet and intranet for their business applications in the following ways:

 

1. Communication and Collaboration:

Without proper communication, no enterprise can run effectively. Enterprises are using gmail, instant messaging apps like Viber and Whatsapp and Video conferencing platforms like Zoom for communication within and out of organization and for collaboration among different teams in the organization.

 

2. Document sharing and management:

Enterprises are using cloud-based storage like Google Drive for document sharing which provides flexibility to store data anywhere and anytime without worrying about carrying your own storage device.

 

3. E-commerce and online payment:

Enterprises are using the internet to sell products and services through e-commerce platforms, reaching a global audience. Secure payment gateways enable online transactions, contributing to the growth of online sales.

 

4. Project Management:

Enterprises are adopting tools such as Jira and Trello which facilitates project planning, tracking, and collaboration among team members in an organization.

 

5. Customer Relationship Management (CRM):

Web-based CRM Systems: Enterprises use internet-based CRM platforms like Salesforce or HubSpot for managing customer interactions, sales, and marketing activities.

 

 

Geographic Information System (GIS) is a powerful technology that uses the visualization, analysis, and interpretation of spatial and geographic data. Some powerful applications of GIS are as follows:

1. Urban Planning and Development:

GIS helps urban planners analyze land use patterns, plan infrastructure development, and optimize city layouts. It  is also used to assess and regulate zoning regulations for residential, commercial, and industrial areas.

 

2. Environment Management:

GIS aids in monitoring and managing natural resources, such as forests, water bodies, and wildlife habitats. GIS is used to assess the potential environmental impacts of proposed projects.

3. Disaster Management and Emergency Response:

GIS assists in identifying areas prone to natural disasters, facilitating proactive risk assessment and planning. It helps emergency responders with real-time mapping and resource allocation during disasters.

 

4. Business Intelligence and Market Analysis:

GIS enables businesses to target customers based on their geographical location and preferences. It is used to analyze potential business locations by considering factors like demographics, competition, and accessibility.

 

5. Public Health:

GIS is used to map the spread of diseases, helping health authorities understand and control outbreaks.GIS assists in planning healthcare facilities and optimizing their locations to improve accessibility.

 

2. What is a transaction processing system? What is the difference between a management information system and an expert system?

 

A transaction processing system (TPS) is a type of information system that facilitates the collection, processing, and storage of transactional data generated by day-to-day business operations. 

It encompasses key characteristics and components such as data input mechanisms for recording business activities, a processing system that applies predefined rules to the data, a centralized database for storage and retrieval, concurrency control mechanisms to handle simultaneous access, robust recovery and backup features for data protection, security measures to ensure data integrity and confidentiality, transaction logging for auditing and troubleshooting, and reporting capabilities for extracting valuable insights from the processed data. Together, these elements contribute to the efficiency, reliability, and overall effectiveness of the TPS in supporting routine business operations.

 

The difference between management information system and expert system are as follows:

 

 

3. Explain the expert system and its use in solving business applications. Explain how data warehousing and data mining tools are used in expert systems for business applications.

 

An expert system is a type of artificial intelligence (AI) system that emulates the decision-making abilities of a human expert in a particular domain. It combines knowledge from human experts with computer-based reasoning to solve complex problems and make informed decisions. Expert systems are designed to capture and apply expertise in a specific field, enabling them to perform tasks that typically require human intelligence and experience.

 

The components of an expert system are as follows:

 

1. Knowledge Base (KB): This is the core of the expert system, containing the domain-specific information and expertise. The knowledge base is created by gathering information from human experts, textbooks, documents, and other relevant sources. It consists of facts, rules, heuristics, and procedures that the expert system uses to make decisions.

 

2. Inference Engine (IE): The inference engine is responsible for processing the information in the knowledge base to draw conclusions and make decisions. It uses reasoning mechanisms such as deduction, induction, and abduction to simulate human-like decision-making processes.

 

3. User Interface (UI): The user interface provides a means for users to interact with the expert system. It can take various forms, including text-based interfaces, graphical interfaces, or natural language interfaces, depending on the design and complexity of the system.

 

4. Explanation System: An explanation system helps users understand the reasoning behind the expert system's decisions. It provides transparency and helps build trust by explaining how the system arrived at a particular conclusion.

 

Expert system are used in the following domains in business applications:

 

1. Decision Support Systems (DSS): Expert systems are integrated into decision support systems to assist managers in making complex decisions. For example, in financial planning, an expert system can analyze market trends and recommend investment strategies.

 

2. Customer Support: Expert systems are used in customer support applications to provide personalized assistance and troubleshooting guidance. They can answer queries, offer solutions to common problems, and escalate complex issues to human experts when necessary.

 

3. Diagnosis and Troubleshooting: Expert systems are widely used for diagnosing problems in various industries, such as healthcare, manufacturing, and IT. They can analyze symptoms and recommend solutions based on the knowledge stored in the system.

 

4. Quality Control: In manufacturing, expert systems can be employed for quality control by identifying defects and suggesting corrective actions. This helps improve product quality and reduce waste.

 

5. Financial Analysis: Expert systems are utilized in financial applications for tasks such as credit scoring, risk assessment, and investment analysis. They can analyze large datasets and make predictions based on historical and current information.

 

Data warehousing is used for the following purposes in expert system:

 

• Data Integration: Data warehousing involves collecting, storing, and managing large volumes of structured and unstructured data from various sources within an organization. The data warehouse acts as a central repository that consolidates information from different departments and systems.

 

• Knowledge Base Enrichment: Expert systems rely on a knowledge base to make decisions. Data warehousing helps in enriching the knowledge base by providing a comprehensive and organized collection of historical and real-time data. This data can be used to update and refine the rules, heuristics, and other components of the expert system.

 

• Data Cleansing and Quality Improvement: Data warehousing processes often include data cleansing and quality improvement procedures. These activities ensure that the data used by expert systems is accurate, consistent, and reliable. Clean and high-quality data contribute to the effectiveness and reliability of the expert system.

 

• Historical Analysis: The historical data stored in a data warehouse enables expert systems to perform trend analysis, identify patterns, and make predictions. This historical perspective enhances the decision-making capabilities of expert systems by allowing them to consider long-term trends and patterns in the data.

 

Similarly, data mining is used for the following purposes in expert system:

 

• Pattern Recognition: Data mining tools analyze large datasets to identify patterns, correlations, and trends. In the context of expert systems, this information can be invaluable for refining rules and heuristics within the knowledge base. The expert system can learn from historical data patterns to improve its decision-making capabilities.

 

• Predictive Modeling: Data mining techniques, such as regression analysis and machine learning algorithms, can be applied to predict future outcomes based on historical data. Expert systems can utilize these predictions to make proactive decisions and recommendations in business applications.

 

• Rule Discovery: Data mining tools can automatically discover implicit patterns and rules within the data. These discovered rules can be incorporated into the knowledge base of the expert system, enhancing its ability to make accurate and context-aware decisions.

 

• Anomaly Detection: Data mining can help identify outliers and anomalies in the data. In business applications, this is particularly useful for detecting irregularities, fraud, or unusual patterns that may require expert system intervention.

 

• Segmentation and Targeting: Data mining enables the segmentation of data into meaningful groups. Expert systems can use this information for targeted decision-making, such as personalized marketing strategies, customized customer support, or individualized product recommendations.

 

 

 

4. Describe the details, which need to be addressed for effective communication between human and computer while designing standard use interfaces.

Designing an interface between human and computer requires careful consideration of both human factors and technical factors. Here are some best practices for designing an interface that promotes clear communication between humans and computers:

1. Keep the user in mind: Design the interface with the user in mind, considering their needs, expectations, and limitations. Use familiar language, and avoid technical jargon.
2. Use clear and concise language: Use simple, concise language that is easy to understand. Avoid using ambiguous or vague terms that could lead to confusion.
3. Provide clear feedback: Ensure that the system provides clear feedback to the user, indicating what action was taken or what error occurred. Use feedback mechanisms such as sounds, animations, or visual cues.
4. Use consistent and intuitive design: Use consistent design throughout the interface to promote ease of use and familiarity. Use intuitive icons and symbols that are easily recognizable and understandable.
5. Test the interface with real users: Conduct usability testing with real users to identify potential areas of confusion or misunderstanding. Use the feedback from testing to refine and improve the interface.
6. Provide user assistance and support: Provide user assistance and support such as online help, documentation, and tutorials to help users better understand the interface and the system.

 

5. Explain multi protocol techniques. What are the features of multi protocol? What are the issues to be focused on communication media for any organization?

 

• In multi protocol technique data is transmitted via labels instead of requiring lookups into complex routing tables. In public internet data is transmitted in the form of packets, where each router receives a packet and based on the destination address performs a lookup in the routing table. But in multi-protocol labeling technique, each packet is sent across a predetermined network path, as a result, the router spends less time deciding where to forward each packet.
• Each packet is assigned to a class called Forwarding Equivalence Class(FEC) and the paths that packets can take are called Label-Switch paths(LSP). Packets are assigned the same FEC travel the same LSP.
• Because MPLS supporting routers only need to see the MPLS labels attached to a given network, MPLS can work with almost any kind of protocol, hence the name multi-protocol.

 

Features of MPLS:

• High speed and efficiency: They use short and fixed length labels to forward packets, avoiding complicated routing table lookups
• Multi-Protocol support: MPLS resides between link layer and network layer. It can work over various link layer protocols(example, Ethernet) to provide connection-oriented services for various network layer protocols(For example, IPv4, IPv6, and IPX).
• Good Scalability: The connection-oriented switching and multilayer label stack features enable MPLS to deliver extended services, such as VPN, traffic engineering, and QoS.

 

some key issues to focus on when selecting communication media:

Internal vs. External Communication:

• Internal communication: Consider factors like employee demographics, preferred communication styles, dispersed teams, information sensitivity, and cost-effectiveness.
• External communication: Tailor your approach to different stakeholder groups (customers, partners, investors, media) with varying interests and information needs.

Channel Richness:

Rich media: Face-to-face meetings, video calls, group presentations offer high clarity and nuance through verbal and nonverbal cues.

 

Lean media: Email, text messages, reports are efficient for factual information, updates, and reminders.

 

Engagement and Feedback:

• Select media that encourage two-way communication and feedback. Consider interactive platforms like polls, surveys, and online forums to foster engagement and gather valuable insights.

Security and Privacy:

• Choose channels with robust security measures to protect confidential information. Implement access controls, data encryption, and clear usage policies to safeguard sensitive data.

 

6. Write Short note on

1. GIS application in business
   1. It is a kind of visual system that is used for mapping, gathering, and analyzing data. It helps find relationships between data patterns that are hard to break in.
      1. Tourism: With GIS tourists can map out areas that will serve their main purpose of traveling. They would find it easy in knowing the best and worst weather conditions, hotels to lodge in, and mode of travel.
      2. Banking: It allows banks to analyze demographic information and pinpoint areas with potential demand for financial services. It also helps evaluate the value of properties attached with the loans by considering factors like neighborhood demographics, proximity to amenities and potential environmental hazards.
      3. Marketing and Sales:
         1. Site selection: Identify ideal locations for new stores or branches based on demographics, competitor analysis, and traffic patterns.
         2. Market Segmentation: Tailor marketing campaigns to specific market segments based on their geographic characteristics and needs.
      4. Supply Chain and Logistics: 
         1. Route Optimisation: Plan the most efficient delivery routes, considering factors like traffic, distance, and delivery windows.
         2. Facility Location: Select optimal locations for warehouse, distribution centers and manufacturing facilities
      5. Operations and Facilities Management:
         1. Asset management: Track and manage physical assets like vehicles, equipment and infrastructures across vast geographical areas

 

2. Information System(IS) for marketing:
   1. It can help us:
      1. Customer insights
      2. Marketing Operations
      3. Market Analysis & Competitive Intelligence

 

• Customer insights
  • Data Collection: System gathers information about the customer from various sources such as CRM, social media engagement, and surveys. This paints a detailed picture of customer demographics, preferences, and behavior.
  • Segmentation & Targeting: Based on the collected data, the marketers can segment the proper target audiences. This allows targeted marketing campaigns with personalized messages and offers
  • Customer Relationship Management(CRM): CRMS systems centralized customer data, interactions, and history, providing a 360-degree view of each customer. This allows personalized interactions, efficient issue resolution, and improved customer loyalty.
• Marketing Operations:
  • Campaign Management: Systems help plan, launch, track and analyse marketing campaigns across various channels like email, social media and paid advertising.
  • Content Marketing: Content Management Systems(CMS) facilitate content creation, scheduling, and publication across different platforms.
  • Marketing Automation: Systems automate repetitive tasks like email marketing, social media posting, and lead nurturing, freeing up marketing teams to focus on strategic initiatives.
• Market Analysis & CompetitiVe Intelligence: 
  • Market Research: Information systems collect and analyse data on trend, competitor activity, and industry news. This helps identify opportunities, threats and inform strategic decision-making.
  • Competitive Analysis: By tracking competitor marketing strategies, pricing, and product offerings, businesses can gain valuable insights and develop differentiated approaches to stay ahead in the market.

3. Information System for Inventory:
   1. Tracking Inventory Levels: Real-time inventory tracking across multiple locations eliminates manual counting errors and provides accurate data on stock levels. This helps avoid stockouts, overstocking, and unnecessary carrying costs.
   2. Order Management: Systems automate purchase orders, track deliveries, and manage returns, streamlining the entire procurement process. This improves efficiency and ensures timely availability of materials.
   3. Demand Forecasting: By analyzing historical data and market trends, IS can predict future demand for specific items. This helps businesses optimize inventory levels to meet customer needs without unnecessary holding costs.
   4. Warehouse Management: Systems manage warehouse layout, optimize picking routes, and track item locations, improving picking and packing efficiency.

 

4. Process-Oriented approach: 
   1. It is a way of thinking and working that focuses on systematically defining and following established procedures to achieve a desired outcome. It emphasized the im;ortance of clearly identified steps, rules, and checkpoints within a well-structured framework.
   2. The process-oriented approach is based on the understanding that the processes must be carefully planned and executed. The better the planning, the better the result of the processes usually is. Thus, predictable and always equally good results are achieved. In modern quality management, the organization is aligned with the processes. 

 

Submitted By:

Akanksha Giri (076BEI004)

Anju Chhetri (076BEI005)

Ankit Shahi (076BEI006)