Information Systems Overview

Information Systems

• Software helps to organize and analyze data.
• Raw data is turned into useful infromation which aids in decision making.
• Information systems are used for collecting, sorting, and processing data.
• An information system provides information, knowledge and digital products.

Using Information Systems

• Provides a means to extract required information by any organization.
• Empowers decision making within the organization.
• Process financial accounts.
• Manage human resources.
• Reach potential customers.
• Involves hardware, software, telecommunications, databases, and human resources.

External and Internal Data

• Internal data is gathered from within an organization.
• Used to make decisions for everyday operation.
• Can be used for sales, finance, marketing, and human resources.
• External data is gathered from sources outside of the organization.
• Useful for studying market trends or other factors before implementing changes.
• Surveys, questionnaires, research and customer feedback are all examples of external data.

Management Information Systems (MIS)

• Used by tactical managers to monitor current performance status.
• Analyzes input to produce reports to monitor, control and predict future performance.
• Summarizes operations.
• Increases operational efficiency.
• Supports key decision-making.
• Key characteristics: Decision support, Data integration, User-oriented.
• Examples include: Sales Management Systems, Budgeting Systems, Human Resource Management Systems.

Decision Support Systems (DSS)

• Interactive software-based systems.
• Helps managers make decisions by using data, analytical models and software.
• It provides support for complex decision making and problem solving tasks. Key characteristics: interactive interface, analytical models, data-driven, flexible and adaptive.

Data Warehousing

• Enterprise data warehouse (EDW).
• Aggregates data from different sources into single, central, consistent data store.
• Supports data analysis, data mining, AI and machine learning.
• Used to run powerful analysis on large amounts of data.

Data Capture: Keying in Data

• Typing in data using a special keyboard.

Data Capture: Bar Codes

• Detects amount of light reflected by dark and light lines.
• Check digits are included.
• Includes country code, company code, and product code.
• Used in EPOS, libraries, luggage routing, stock taking, cinemas etc.

Data Capture: Magnetic Stripe Cards

• Information is stored on magnetised stripes.
• Has account number and expiry date on the card.
• Accurate and fast way of capturing data
• Used for ATM, EPOS.

Data Capture: Radio Frequency Identification (RFID)

• Uses radio waves to passively identify a tagged object.
• Used for tracking items.
• Tags use radio waves to communicate their identity and other information.
• Readers get signals back from RFID tag.

Data Capture: Near Field Communication (NFC)

• Short-range wireless technology.
• Transfers information between devices quickly.
• Used for sharing content.
• Establishes wireless connection.
• Can pair devices together.
• Connects Bluetooth enabled devices.
• Connects to networks.

Data Capture: Quick Response (QR) Codes

• A type of barcode which contains more information than traditional barcodes.
• Stores information as a series of pixels in a square-shaped grid.
• Can be used for menus or posters.

Data Capture: Smart Cards

• A physical card with embedded integrated chip.
• Physical contact or RFID or NFC is required.
• Chips can be a microcontroller or embedded memory chip.
• Tamper-resistant, enabling Encryption.
• Used for EPOS.

Internet of Things (IOT)

• A network of physical devices, vehicles, appliances and other items.
• Has sensors, software, connectivity capabilities.
• Can connect and exchange data with each other and with central systems.
• Used to monitor, manage and automate functions remotely.
• Examples are: smart lightbulbs, thermostats, locks, refrigerators, security camera systems, etc

Negligence in an IS environment

• Failure to exercise the appropriate level of care and diligence expected to safeguard and manage information systems.
• Lapses in security measures.
• Lapses in maintaining backups.
• Lapses in preparing for potential disruptions.
• Effects of negligence: data loss, security breaches, natural disasters.

Mitigation of Negligence

• Facility Security, Access Control, Data Security, Internal Security, Network Security, and Software and System Security are necessary to mitigate negligence.

Training Issues

• Enhanced productivity.
• Better security compliance.
• Improved communication.
• Supporting innovation.

Training Requirements

• Training requirements vary depending on the type of staff.
• Managerial staff require strategic use of ICT, decision-making tools, cybersecurity awareness, and change management training.
• Technical staff require technical proficiency, system administration, cybersecurity skills, and problem-solving training.
• Administrative staff require basic ICT skills, data management, communication tools, and cybersecurity best practices training.

Training Methods

• Training could be through: Workshops, Seminars, Courses Professional development programs, E-learning, Intensive hands-on workshops, Certification programs or, Online courses with practical labs and simulations, On-the-job training, Short courses, Webinars, and Computer-based training modules.
• Computer-based training (CBT) allows participants to learn at their own pace and is easily accessible.
• CBT is often more affordable and has consistent content, has advantages and disadvantages.
• Instructor-led training (ILT) is highly interactive, allows for collaboration opportunities and real-time interaction, has advantages and disadvantages.