Understanding Information Systems

• Computers and information systems are all around, including online classes, grocery and retail, smartphones, and the Internet.

Information Systems (IS)

• A set of interrelated components working together
• Designed to collect, retrieve, process, store, and distribute information
• Aims to facilitate planning, control, coordination, analysis, and decision-making in business organizations

Major Components of an Information System

• Information Technology (IT) is the means by which data is transformed and organized for business use
• IT utilizes hardware and software to facilitate business activities.

Hardware

• Tangible technology
• Used to manage data
• Examples include computers, smartphones, and their components

Software

• Intangible programming
• Directs hardware and enables users to perform specific tasks.

Data source

• Houses data that can be retrieved, manipulated, and analyzed for decision-making
• Examples include databases and data warehouses.

Telecommunications

• Pathways through which devices and software can send data to each other.

Human expertise

• Provided by data analysts and other experts
• Crucial for improving processes, since not everything can be handled by robots

People

• Users of IS or "actors" who interact in a business process
• Systems analysts, programmers, CS/IS research scientists, network & system admins, database admins, software engineers, security analysts, web developers & network architects are types of people

Organization

• A collection of functional units working together to achieve a common goal

Business processes

• Goal-oriented activities conducted by a business
• Involves defining objectives, creating and analyzing alternatives, involving and assigning stakeholders, testing processes, and analyzing results

Data

• Raw and unorganized facts

Information

• Collection of facts organized to have additional value
• A set of processed data in a meaningful way according to the given requirement.
• Processed, structured, or presented in a given context to make it meaningful and useful.
• Is the output of an information system
• Quality depends on timeliness, integration, consistency, accuracy, and relevance

Data vs. Information

• Data consists of variables that help to develop ideas/conclusions
• Information is meaningful data
• Data can be text and numerical values
• Information relies on data
• Data does not depend on information
• Bits and bytes are the measuring unit of data
• Information is measured in meaningful units like time or quantity
• Data can be easily structured
  • Tabular data
  • Graphs
  • Data trees
• Information can be
  • Language
  • Ideas
  • Thoughts
• Data does not have any specific purpose
• Information carries a meaning assigned by interpreting data
• Data does not directly help with decision-making
• Information helps in decision making
• An example of data is student test score
• An example of information is the average score of a class that is derived from given data

Information Concepts

• A process is a set of logically related tasks performed to achieve a defined outcome
• The value of information is directly linked to how it helps decision-makers achieve their organization's goals.
• Knowledge
• Awareness and understanding of a set of information
• And ways that information can be made useful to support a specific task or reach a decision
• (Knowledge >> Understanding >> Wisdom)
• A system consists of a set of elements or components that interact to accomplish goals

Computer Based Information Systems (CBIS)

• Hardware: Computer equipment
• Software: Computer programs
• Databases: Organized collections of facts; heart of an information system
  • Collections of all relevant data organized in a series of integrated files
  • They are essential for the success of any information system
  • Databases are managed with a database management system (DBMS) - e.g., Oracle
  • They reduce personnel time needed to gather process, and interpret data manually
• Databases are organized collections of structured information/data, typically stored electronically
• Telecommunications: Electronic transmission of signals for communication
• Networks: Distant electronic communication
• Internet: Interconnected networks
• Intranet: Internal corporate network
• Extranet: Linked intranets
• People
• Procedures: strategies, policies, methods, and rules for using a CBIS

Examples of Information Systems

• A university: Stores student data in a database with built-in query capability
• Retail Store: Stores data on products, suppliers, sales, and costs, using process components and forecasting models

Importance of Information Systems

• Increased Efficiency and Productivity through automation and data management
• Enhanced Decision-Making with data analytics and real-time information
• Innovation and New Business Models via digital transformation and improved agility
• Customer Relationship Management through personalization and feedback loops
• Supply Chain Optimization via better integration and inventory management
• Job Creation and Transformation with the rise of new roles and skill shifts
• Security and Compliance via cybersecurity measures and risk management
• Cybersecurity: With increased reliance on information systems, businesses must invest in cybersecurity measures to protect sensitive data and comply with regulations
• Risk Management: IS help organizations identify and mitigate risks associated with data breaches and other threats

Using Information Technologies for a Competitive Advantage

• Changes industry structure and transforms the rules of competition
• Creates competitive advantage
  • By offering companies ways to outperform their rivals
• It spawns whole new businesses, often from within a company's existing operations
  • Information systems
  • Help organizations reduce the cost of products and services
  • Assist with differentiation and focus strategies
  • Can help bottom-line and top-line strategies
• Enterprise systems
• Supply chain management (SCM)
• Customer relationship management (CRM)
• Enterprise resource planning (ERP)
• Collaboration software
• Differentiation strategies
• Make products and services different from competitors. Example: Apple, Amazon.com
• Focus strategies
• Concentrate on a specific market segment
• Attempt to achieve a cost or differentiation advantage. Examples: Apple, Abercrombie & Fitch, Nordstrom

BIS Systems

• Definition: An interrelated set of business procedures used within one business unit working together for a purpose, confined within an environment and separated by a border.
  • The system includes parts that work together to achieve a goal or task.
• Examples
  • Solar system
  • Digestive system
  • Public transport system
  • Central heating system
  • Computer system
  • Information system
• Objects: Set of objects and relationships viewed as a whole
• Entities
• Describes a system in terms of objects (entities), attributes, events activities, and processes
• A system can be described in terms of objects (entities), attributes, events, activities, and processes
• Is something of interest in the system.
• Denote a property or characteristic of an object or describes an aspect of an object
• Anything that occurs at an instance in time t and changes the state of the system.
• An action that occurs over an interval of time including a start and stop .
• The sucession of state of an object over a span of contiguous succession of one or more intervals.

Characteristics of a System

• Components: Include hardware, software, database, networks, and users in an information system.
• Interrelated Components: The parts work together and depend on each other; example: software processes data stored in the database and displays it to users through the network.
• Boundary: Separates the system from the outside world; example: An internal company network separated from the internet by a firewall.
• Purpose: Is the reason why a system exists; example: An information system is designed to manage, process, and share company information efficiently.
• Environment: Everything outside the system that can affect it; example: Customers, suppliers, competitors, and government regulations affecting the information system.
• Interfaces: How the system connects and interacts with its environment
  • Example: A company website allows customers to place orders (input data into the system)
• Constraints: Rules or limits that the system must follow
  • Example: Data privacy laws like GDPR or system storage limitations
• Inputs: What the system receives to work on (e.g., data or commands)
  • Example: Customer details entered through an online form.
• Output: What the system produces after processing the input.
  • Example: A sales report generated for management based on customer orders.
• A subsystem is simply a system within a system
  • An automobile is a system composed of subsystems; engine system, body system, frame system

System Types

• Open System: System which has exogenous activities.
• Closed System : System which has no inputs (exogenous activities) and no outputs.
• Continuous System: System in which the changes are predominantly smooth. Example: A missile system.
• Discrete System: System in which the changes are predominantly discontinuous. Example: A factory system.
• Adaptive System: System which reacts to changes in its environment.
• Nonadaptive System: System which does not react to changes in its environment.

Important System Concepts

• Decomposition
  • Process of breaking down a system into smaller components. Allows the system analyst to break a system into small manageable subsystems
  • Focus on one area at a time, concentrate on component pertinent to one group of users and build different components at independent times
• Modularity
  • Divides a system into modules of a relatively uniform size, simplifying system design
• Coupling Subsystems that are dependent upon each other are coupled
• Cohesion Extent to which a subsystem performs a single function

System Analysis and Design

• Systems Analysis means understanding and specifying in detail what an information system should do
• System Design has to do with specifying in detail how the parts of an information system should be implemented
• System Analysis and Design are crucial elements in the development of any information system.
• Improved Efficiency and Productivity
  • Thoroughly analyzing and designing systems
  • Organizations can ensure that the final product is optimized for performance, reducing redundancies and increasing efficiency, helping to achieve better productivity and resource utilization
• Clear Understanding of Requirements
• System analysis helps in gathering detailed requirements from stakeholders, ensuring stakeholders meet their needs
• It helps in identifying what the system should do, how it should perform, and the constraints it must operate under
• Risk Reduction
• Analysis and design help in identifying potential risks early in the development process.
• Can include technical challenges, scope creep, or integration issues, allowing teams to mitigate these risks before they become major problems.
• Enhanced Quality
  • A well-designed system is more likely to meet quality standards and user expectations
  • Results in fewer errors and bugs, better user satisfaction, and lower maintenance costs.
• Cost Management
  • Investing time in system analysis and design can save money by preventing rework and ensuring budget is met
• Facilitates Communication
• A clear analysis and design document serves as a communication tool among developers, project managers, and end-users
• Ensures everyone is on the same page, reducing misunderstandings and conflicts.
• Scalability and Flexibility
• A good system design considers future needs and potential changes
• This makes it easier to scale and adapt the system as requirements evolve, ensuring long-term usability and relevance
• Compliance and Security
  • Analysis and design ensure that the system adheres to regulatory requirements and security standards, protecting sensitive data and maintaining compliance with legal guidelines

When to use systems analysis and design

• To correct problem in existing system
• To improve the existing system
• Usher in a new system
• Outside group may mandate change
• Competition can lead to change

System project overview

• Scope Definition - Is the project worth looking at?
• Problem Analysis - Is a new system worth building?
• Requirements Analysis - What do the users need and want from the new system?
• Logical Design - What must the new system do?
• Decision Analysis - What is the best solution?

System Analysis

• Systems analysis defines the problems to be solved and provides the architecture of the proposed system
• Analysis is defined as the procedure by which a whole is broken down into parts

System Analysis Techniques

• Logical Data Modeling
• Identifies data requirements of the system being designed
• Separates the data into entities and relationships
• Data Flow Modeling
• Identifies how data moves around an information system
• Examines processes, data stores, external entities, and data flows
• Entity Behavior Modeling
• Identifies the events that affect each entity and the sequence in which these events occur.

Reasons for systems projects

• Improved service, better performance, more information, stronger controls, and a reduced cost are reasons for systems projects.

Factors that affect systems projects

• Internal factors
• Strategic plan, top managers, user requests, information technology department, existing systems
• External factors
• technology, supplier, customers, competitors, the economy, the government

Systems Development Life Cycle (SDLC)

• Feasibility Study - Measures how suitable system development systems will be for the company, through four feasibility Tests
• Operational Feasibility - Can the system work well in the company?
  • Example: Will employees easily use the new online booking system?
• Technical Feasibility - Does the company have the right technology and skills?
  • Example: Does the IT team know how to build a mobile app?
• Schedule (time) Feasibility - Can the company finish it on time?
  • Example: Can the new payroll system be ready before the next financial year?
• Economic Feasibility (Cost-Benefit Analysis) - Will the benefits be worth the cost?
  • Example: Will the money saved by using a new inventory system be more than the cost of making it?

Systems Development Life Cycle (SDLC)

• Planning phase
  • Review project requests
  • Prioritize project requests
  • Allocate resources, and identify project development team
  • Identify business value as well as analyze feasibility
  • Develop a work plan and staff the project, as well as control and direct
• Analysis phase
  • Conduct preliminary investigation
  • Find the exact nature of problem or improvement and whether the project is worth pursuing.
  • Present findings in feasibility reports or studies
  • Perform detailed analysis activities including studying current systems to determine user and implement solution requirements and recommendations
• Design phase
• Assess feasibility of each alternative solution and how system will be developed
• Recommend the most feasible solution
• Design Selection, Architecture design, Interface design, data storage design and program design
• Implementation phase
  • Construction and develop programs
  • Install and test new system as well as program and system testing
  • Installation with training conversion
  • Training and support plans

Systems Analysis

• Problem Identification: Identify the issues the system aims to address
• Requirements Gathering: Communicate with customers and developers to gather system design information
• Feasibility study: The evaluation of several factors such as , technical, operational, and financial aspects to determine the feasibility of the proposed solution
• Analysis and modeling: Develop models to help customers visualize systems and their interactions Data flow diagrams(DFD) Use cases Entity-Relationship(ER) Diagrams(ER)
• Scope Definition: Prevents excess features and ensures the project stays within limits
• Architectural Design– Determines the overall structure and components of the system
• Component Design– Designing individual components and their interactions.
• Interface Design- Specifying the interfaces between components and external systems.
• Data Design - Designing the database schema and data structures.
• Detailed Design– Creating detailed specifications for each component, including algorithms and data flow.

Techniques Used

• Unified Modelling Language (UML)– A standardized modelling language
• Used to visualize, specify, construct, and document software systems
• Data Flow Diagrams (DFDs)– Diagrams that illustrate the flow of data through a system
• Entity-Relationship Diagrams (ERDs)– Diagrams that represent the entities and relationships between them in a database
• Decision Trees- Diagrams that show the possible outcomes and decisions in a process.
• State Transition Diagrams- Diagrams that represent the different states a system can be in and the transitions between them.

Key Differences Between System Analysis and System Design

• System Analysis focuses on understanding the problem domain and gathering requirements
  • Output: Requirements document
  • Techniques: Interviews, Surveys, observation, document analysis
  • High-level understanding
• System Design focuses on designing the system and specifying the solution
  • Output: System design specifications
  • Techniques: UML, DFDs, ERDs, decision trees, state transition diagrams, high-level understanding
  • Detailed specifications

Competing in the Information Age

• Internet of Things (IoT) is defined as:
  • A world where interconnected internet-enabled devices or "things" have the ability to collect and share data without human intervention.
  • Is the embedding of technology in everyday objects. Smart home hubs already allow people to use their smartphones to control everything from lighting to kitchen appliances
  • Transforming business, providing intelligent data and automation, creating demand for more skilled workers, and enabling remote working.
  • Examples: Smart Home, Wearable health devices, connected cars and smart cities
• Machine-to-Machine (M2M) - Refers to devices that connect directly to other devices Examples. Smart grids

Data vs. Information

Data is the plural of datum, although data is commonly used to represent both singular and plural forms. Data are raw facts or observations.

• Examples Is Data collected from a spacecraft launch? Electronic transmissions of data (telemetry) from thousands of sensors are converted to numeric and text data by computers
• buying a car or an airline ticket also produces a lot of data.
• The core drivers of the Information Age are as follows -Data- Raw unorganized facts -Information-Data that is organized -Business Intelligence-Analyses patterns and relationships -Knowledge- Using skills to take full advatage of Information and intelligence
• To make effective and timely decisions, managers must often first process data to find the information they need

The Process of Managing Data for Effective Decision-Making

• Gathering data

  • Internal and external data may be input into the system by employees or collected electronically from different sources

• Receiving data

  • Data analysts, assisted by computer algorithms ( a type of artificial intelligence) help sift and store incoming data in relevant areas. A system that links all types of data is the most useful because it allows different data sets to be compared

• Handling data

  • Managers who process data on a variety of topics to make decisions need the data to be relevant, accurate, and up-to-date and the retrieval process to be speedy and efficient

• Reviewing data

  • Ideally, the data in a data management system will be organized in such a way that managers can retrieve what they need quickly, check that data is current and accurate, and compare it with other data in order to turn it into information

• Acting on information

  • An efficient management system can quickly sift through data to produce reliable information. This helps managers make decisions and react more quickly, for instance, to changing customer preferences giving a company a competitive edge. In most cases, however, a manager's experience in analyzing data remains invaluable

• "DIKW model" describes how information stems from data, knowledge from information, , and wisdom from knowledge. (Data, Information, Knowledge, and Wisdom)

• Linear process of analyzing and understanding makes good decisions. Data can be presented as facts, symbols, measurements, numbers, or observations

• Needs context to be meaningful which can be achieved when organized, interpreted, or verified.

• Decisions can be made more effectively by gleaning information from the data.

• Enterprise Data Management (EDM) is concerned with defining, integrating, retrieving, and managing data.

• General Data Protection Regulation (GDPR) is a European law governing the use of data from which a person can be identified.

• Structured data is easily classified while unstructured data is more difficult to analyze

"Big Data" Analysis

• Businesses obtain large amounts of customer data online and are trying to harness it.
  • The data can be used to create detailed profiles to target cutomers more precisely
• It comes from data collected from systems, translating information about employees, production lines, and markets
• Customer data collection includes tracking customer buying preferences and habits with accuracy
• Transmitted by big data
• Includes database statistics to video, audio, and email documents

Types of Data

• External Data: Ever expanding data generated by outside organizations to be increasingly valuable
  • Includes data from social media, Audio, Photos and video, and data shared outside the company(press, job descriptions, etc.)
  • Big Data Vendors: Provide services, systems and tools for companies to store, access and analyze data as well as tailor applications to user businesses
• External systems
  • Apache Hadoop: Open-source software library for storing and processing big data
  • Petabyte: Unit of digital data equivalent to 1,024 terabytes
  • Exabyte: Unit of digital data equivalent to 1,024 petabytes (five exabytes equates to all words ever spoken by human beings)
• The word "data" is the plural of the word "datum". That's useful for pub trivia and Scrabble only.

Different Systems

• Big storage hardware: Servers, storage and network equipment
• Software: Programs for research etc
• Cloud services: storage networks

Characteristics of "Big Data"

Variety systems, and software

• Veracity: Determine data with specific context, must keep data clean and implement data
• Volume: The scale of data, data is generated daily and created by machines and networks
• Velocity: Analysis of streaming data

Examples

• Feedback: Customer feedback comes in various forms
• Structured data: Data gathered for a set purpose
• Social Media: Algorithms to deal with social media and related factors , challenging accuracy with particular posts
• Social Media: generates enormous amounts of data through shares
  • Generates big data, requiring the means for its analysis.
• In real time Market Data: In real time stock market trading involves a rapid exchange of financial data demonstrating big data's velocity. "Big Data" Requires Analysis
• “Big data” can be used for market research purposes to track and target consumers

Progressive Corp.

• uses “big data” to increase revenue by offering lower car insurance premiums to drivers who install a diagnostic port in their car, measuring speed and acceleration, sending data via GPS signal.
• TiVo uses “big data” to create new revenue, collecting TV viewing habit data via boxes connected to the Internet, then selling the data to advertisers correlating data and sales figures Amazon Data Usage
• Amazon US online retailer, collects browsing histories, and purchasing data, using “cookies,” text files saved in a customer's browser, determining customer interest to send recommendations and create additional sales and enabling quick customer recalls, speeding ID details and increasing customer satasfaction

Structured & Unstructured Data

• Have type formatted as custom: Have defined length: number, dates etc
• Created from a source such as, Sensor Reading, machine or human interaction
• Example: Customer databases and email connect, Customer ID, Name, and emails make the example

Reports

• A document containing data organized in a table, matrix, or graphical format allowing users to easily comprehend and understand information
• Changes occur, example is with stock market data
• Static: Created once based on data that isn't changeable, example is with static report

IoT

• What types of IoT next 10 years (Smart appliances, Connected Cars, and wearable health devices)
• What Data do IoT collect (Environmental data, health and fitness Data Security Data)
• Structured vs Unstructured Organization

Buisness Intelligence and Its Functions

• All information collected from multiple sources
• Intelligence and wisdom all have their roles

Need to Know

• Star scheme: Simplest format of online analytical processing (OLAP) in data warehouse
• The quality of the master data should be kept complete
• Slice and dice: Process in which data is broken down to help analysis
• Analytics: Science of fact based decision
• Business analytic: Scientific process of transforming data into insight for making better decisions -data quality should be complete accurate

Skills Needed

• Skills needed is to understand of the data to become a coder and understand math and business -Data scientist: Extracts knowledge from data by performing statistical analysis, data mining, and advanced analytics identifying trands and market changes etc
• Buisness intelligence tools need to be specific ###Digital tools
• Digital Dashboard: tool tracks the percentage of people who open on a website and make purchases Four categories of analytics" descriptive data diagnostic analytics predictive and precriptive
• Knowladge : Skills and expertise which provide the ability to form an intelligent recourses
• What kind of assets help harnes the weth of knowladge

Systems thinking and management IS

• It is best for Common departments to work independently

MIS Department Roles and Responsibilities

• Chief Security Officer (CSO) - Security of business systems strategies
• Chief Technology Officer (CTO) - Speed and acuracy

Increased levels will need (Automation or Digital trans )

New Technologiis

A Changing World

• IT is rapidly evolving in many fields
• Including cloud and entprise cloud platform
• Buisnesses are use IT to make sensitive info that increases data and management to have IT managment Cloud computing: 1/3 of IT budget Data: vast world of over 2.5 B per day for daily use Al: 20% percent job will be lost in current IT. skills change in these fields is a change that is required

Disruptive Technology

Digital Darwinism

• Is the concept of an organization that change for customers as needs happen overtime
• Every organization needs new technologies
• Apple and Netflix are good examples