Chapter 1
What is a business information system?
set of interconnected components that work together to collect, process, store, and distribute information to support decision-making, coordination, control, analysis, and visualization in an organization
What are the hardware components of information systems?
•Central Processing Unit (CPU)
•Memory (RAM)
•Storage Devices (Hard Disk Drive, Solid State Drive)
•Input Devices (Keyboard, Mouse, Scanner)
•Output Devices (Monitor, Printer)
•Communication Devices (Network Interface Card, Modem)
Whats the difference between commercial and open source systems?
COMMERCIAL
•Developed and supported by a software vendor.
•Offers dedicated support and regular updates.
•May come with licensing fees or subscription costs.
•Provides some assurance of quality and reliability.
OPEN SOURCE
•Developed and maintained by a community of contributors.
•Freely available and customizable.
•Relies on community support and updates.
•May require more technical expertise for implementation and troubleshooting.
•Offers flexibility and cost savings.
What are the challenges in data management?
•Data security and privacy - Protecting sensitive data from unauthorized access and breaches.
•Data integration - Combining data from multiple sources and formats into a unified view.
•Data quality - Ensuring data accuracy, completeness, consistency, and reliability.
•Data governance - Establishing policies, processes, and controls for data management.
•Data storage and scalability - Managing large volumes of data and ensuring efficient storage and retrieval.
•Data compliance - Adhering to legal and regulatory requirements regarding data handling and storage
Future trends
•Artificial Intelligence (AI) and Machine Learning (ML) integration for advanced analytics.
•Cloud-based data management and analytics solutions for scalability and flexibility.
•Increased focus on data privacy and security regulations.
•Real-time data analytics for immediate insights and decision-making.
•Internet of Things (IoT) data management and analytics for connected devices.
•Natural Language Processing (NLP) for analyzing and understanding textual data
What are the components of an information system?
•Hardware: Physical devices such as computers, servers, and networking equipment.
•Software: Programs and applications that enable data processing and information management.
•Data: Raw facts and figures that are processed and transformed into meaningful information.
•Procedures: Rules and guidelines that govern the operation and use of the system.
•People: Users who interact with the system to input, process, and retrieve information.
•Networks: Communication channels that enable the transfer of data and information between system components
What are the software components of information systems?
•Operating System (e.g., Windows, macOS, Linux)
•Application Software (e.g., Microsoft Office Suite, Adobe Photoshop)
•Utility Software (e.g., Antivirus, Disk Cleanup)
•Programming Languages (e.g., Java, Python)
•Database Management Systems (e.g., MySQL, Oracle)
Factors to consider
•Business Needs: Consider the specific requirements and goals of your organization.
•Budget: Evaluate the financial resources available for implementation and maintenance.
•Scalability: Determine if the solution can grow with your business.
•Support: Assess the level of support and maintenance required.
•Security: Consider the data protection measures provided by the solution.
•Integration: Evaluate the compatibility with existing systems and applications.
•User-Friendliness: Consider the ease of use and training required.
•Future Proofing: Anticipate future needs and technological advancements.
•Vendor Reputation: Research the reputation and track record of the provider.
•Regulatory Compliance: Ensure the solution meets relevant industry regulations and standards.
What is the data analytics process?
•Define the problem and objectives.
•Data collection and preparation.
•Data exploration and analysis.
•Data modeling and algorithms.
•Evaluation and interpretation of results.
•Decision making and action
Ch 5. Information systems for e-commerce and e-business:
WHAT ARE INFORMATION SYSTEMS FOR E-COMMERCE AND E-BUSINESS?
•Information systems for e-commerce and e-business refer to the technologies and tools that are used to manage and support online business activities.
•These systems enable organizations to conduct online transactions, manage customer relationships, and streamline business processes
What are the types of business information systems?
•Transaction Processing Systems (TPS): Record and process routine transactions such as sales, purchases, and payments.
•Management Information Systems (MIS): Provide reports and summaries of operational data to support managerial decision-making.
•Decision Support Systems (DSS): Assist in complex decision-making by analyzing data and providing insights and recommendations.
•Executive Support Systems (ESS): Provide strategic information to top-level executives for planning and decision-making.
•Enterprise Resource Planning (ERP) Systems: Integrate and manage core business processes and data across functional areas.
•Customer Relationship Management (CRM) Systems: Manage customer interactions and support sales and marketing activities.
•Supply Chain Management (SCM) Systems: Coordinate and optimize the flow of goods, services, and information across the supply chain
What are the networks in information systems?
•Local Area Network (LAN)
•Wide Area Network (WAN)
•Wireless Network (Wi-Fi)
•Internet
•Intranet
•Extranet
•Virtual Private Network (VPN)
Ch. 4
Data management analytics: What is data management?
•Data management refers to the process of collecting, storing, organizing, and maintaining data in a structured manner.
•It involves ensuring data quality, security, and accessibility for efficient use and analysis
What are the BENEFITS OF DATA MANAGEMENT AND ANALYTICS?
•Improved decision-making - Data-driven insights enable better decision-making and strategic planning.
•Enhanced efficiency and productivity - Streamlined data management processes and automated analytics improve efficiency.
•Identifying trends and patterns - Data analysis helps identify trends, patterns, and correlations for better forecasting and planning.
•Cost savings - Optimized data storage and analysis reduce costs associated with data management.
•Competitive advantage - Leveraging data effectively can provide a competitive edge in the market
What are the TYPES IS FOR E-COMMERCE AND E-BUSINESS?
• Ecommerce Platforms: These systems provide the infrastructure for online stores, including website design, product catalog management, and payment processing.
•Customer Relationship Management (CRM) Systems: CRM systems help organizations manage and analyze customer data to improve customer satisfaction and loyalty.
•Supply Chain Management (SCM) Systems: SCM systems facilitate the coordination of activities involved in the production, distribution, and delivery of products and services.
•Enterprise Resource Planning (ERP) Systems: ERP systems integrate various business functions, such as finance, human resources, and inventory management, into a single system.
•Business Intelligence (BI) Systems: BI systems collect and analyze data to provide insights and support decision-making.
•Content Management Systems (CMS): CMS systems enable organizations to create, manage, and publish digital content on their websites.
•Payment Processing Systems: These systems handle online payment transactions securely and efficiently
What are the benefits of an information system?
•Improved Efficiency: Automation of routine tasks and streamlined processes.
•Enhanced Decision-Making: Access to real-time data and analytical tools.
•Increased Productivity: Collaboration and communication tools for efficient teamwork.
•Better Customer Service: Improved tracking and management of customer interactions.
•Competitive Advantage: Strategic insights and data-driven decision-making.
•Cost Savings: Reduction in manual labor and paperwork.
•Improved Data Security: Centralized data storage and access controls
Information system alternatives: What are the differences between server and cloud hosted systems?
SERVER HOSTED
•Requires physical servers to be set up and maintained on-site.
•Provides full control and customization options.
•Requires IT staff to manage and troubleshoot server issues.
CLOUD HOSTED
•Uses remote servers hosted by a third-party provider.
•Offers scalability and flexibility.
•Allows for easy access from anywhere with an internet connection.
•Reduces the need for on-site hardware and maintenance.
•May have limited customization options.
•Relies on the provider for security and uptime.
What are the types of databases?
•Relational databases - Data is organized into tables with rows and columns, and relationships are established between tables.
•NoSQL databases - Designed to handle unstructured and semi-structured data, providing flexibility and scalability.
•Object-oriented databases - Store data as objects, including attributes and methods, allowing for complex data structures.
•Hierarchical databases - Organize data in a tree-like structure, with parent-child relationships.
•Graph databases - Represent data as nodes and edges, ideal for analyzing complex relationships
What are the DATA MANAGEMENT BEST PRACTICES?
•Establish clear data policies and governance.
•Ensure data quality through regular checks and validation.
•Implement data security measures to protect sensitive information.
•Regularly backup and maintain data to prevent loss.
•Adopt data integration techniques for a unified view of data.
•Train employees on data management practices and tools
What are the benefits and challenges?
Benefits
•Increased efficiency and productivity in business operations
•Improved customer experience and satisfaction
•Enhanced data security and privacy
•Better inventory management and supply chain visibility
•Access to real-time analytics and business insights
•Expanded market reach and global presence
•Streamlined order processing and fulfillment
Cost savings through automation and process optimization
Challenges
•Integration with existing systems and legacy infrastructure
•Data integration and management
•Security and privacy concerns
•Scalability and performance issues
•User adoption and training
•Continuous system updates and maintenance
•Keeping up with evolving technology trends
•Cost of implementation and ongoing support
What are the challenges and future trends when implementing information systems?
• Challenges!
Cost: Initial investment and ongoing maintenance expenses.
•Resistance to Change: User resistance and reluctance to adopt new technologies.
•Integration Issues: Compatibility with existing systems and data migration challenges.
•Data Quality and Governance: Ensuring accuracy, integrity, and security of data.
•Training and Skill Gaps: Providing training and support for system users.
•System Reliability and Downtime: Ensuring system availability and minimizing disruptions.
•Scalability: Ability to handle increasing volumes of data and users
Future Trends
• Big Data Analytics: Leveraging large volumes of data for insights and decision-making.
•Cloud Computing: Accessing and storing data and applications over the internet.
•Mobile Technologies: Enabling anytime, anywhere access to information and systems.
•Artificial Intelligence (AI) and Machine Learning: Automating tasks and improving decision-making.
•Internet of Things (IoT): Connecting devices and sensors to collect and exchange data.
•Blockchain Technology: Secure and transparent record-keeping and transactions.
•Cybersecurity: Protecting data and systems from threats and breaches
What's the difference between customer developed and commercial off the shelf?
CUSTOM DEVELOPED
•Tailored to specific business needs.
•Offers full control and customization.
•Requires more time and resources for development and maintenance.
•Can be more expensive in the long run.
OFF-THE-SHELF
•Pre-built software or solutions.
•Offers ready-to-use functionality.
•Requires less time and resources for implementation.
•May not fully meet all business requirements.
•May require additional customization or integration.
•Can be more cost-effective for smaller businesses.
What are data analytics?
•Data analytics involves the extraction, transformation, and analysis of data to gain insights and make informed decisions.
•It includes various techniques such as statistical analysis, data mining, machine learning, and predictive modeling
What are the data analytics techniques?
•Descriptive analytics - Summarizes and describes the characteristics of data.
•Diagnostic analytics - Analyzes data to understand the reasons behind past events or outcomes.
•Predictive analytics - Uses historical data to make predictions about future events or outcomes.
•Prescriptive analytics - Recommends actions based on predictive models and optimization techniques.
•Text analytics - Extracts insights from unstructured textual data.
•Social media analytics - Analyzes social media data to understand trends and sentiment
Key considerations for information system selection and trends
•Business requirements and goals
•Scalability and flexibility of the system
•Integration capabilities with other systems
•User-friendliness and ease of customization
•Security features and compliance with regulations
•Vendor reputation and support services
•Total cost of ownership (including implementation, licensing, and maintenance costs)
Trends
•Mobile commerce (m-commerce) and responsive design
•Artificial Intelligence (AI) and machine learning for personalized shopping experiences
•Blockchain technology for secure and transparent transactions
•Voice commerce and virtual assistants
•Internet of Things (IoT) integration for smart inventory management
•Augmented Reality (AR) and Virtual Reality (VR) for immersive shopping experiences