BPDT QUIZ 1
Session 1 Summary
IT= Technology (Tools, Hardware, software, network)
IS= IT + People + Process + Structure
Hierarchy= Data–(Connectedness) → Information– (Usefulness) → Knowledge → Wisdom
Data= Codified raw facts are recorded events stored digitally as letters and numbers.
Information= When it is processed, structured, or given meaning, making it interpretable.
Information Literacy= The ability to recognize information essential managerial skill.
Business Uses of Information= Communication, process support, decision and a product.
Business process: Set of coordinated activities that lead to a specific goal or outcome
Session 2 Summary
System= Interconnected components processing inputs into outputs to achieve a goal.
Characteristics system: Goal-oriented and Interrelated components working together.
IS Processing Cycle= Input (data collection), Processing (data transformation), Storage (data retention), Output (usable information), and Control (ensuring accuracy).
Elements IS= Data (raw facts), Hardware (physical devices), Software (instructions), Communication Media (networking tools), Procedures (usage guidelines), People (users).
Open systems= Interact with their environment, exchanging information and adapting to changes.
Closed systems= operate in isolation with minimal external interaction.
Feedback & Control= Ensuring proper IS operation, often using feedback loops.
Why Information Systems= Efficient data collection, storage, processing, and retrieval.
Business Rule: Defines or restricts business operations to control behavior.Michael Porter’s Value Chain: A model that breaks down a business into primary (inbound logistics, operations, outbound logistics, marketing & sales, service) and support activities (firm infrastructure, HR management, technology development, procurement) to analyze competitive advantage.
Business Process: A coordinated set of activities involving many people and decisions, often spanning multiple organizations, to achieve a specific goal.
Process Modeling: Mapping processes to understand their structure and interrelations.
Process Improvement (BPR): Redesigning cross-functional processes to eliminate silos.
Business Process Reengineering (BPR): Fundamental rethinking, radical redesign, and dramatic improvement of business processes.
Goals of BPR: Effectiveness (meeting expected outcomes), Efficiency (speed of process completion), Internal Control(data accuracy/security), Compliance (adherence to regulations).
Improving Processes: Identify key processes, assess necessity, leverage IT for improvement, and evaluate redesign impacts.
Levels of Change: Automate (increase efficiency), Informate (enhance decision-making), Transform (fundamentally redesign processes).
Session 3 and 4
Enterprise Information Systems (EIS)
Types of Information Systems:
Personal Applications= Enhance individual efficiency and productivity.
Transaction Processing Systems (TPS) – Handle large volumes of transactional data from business processes.
Functional & Management Information Systems – Support specific organizational functions (e.g., finance, HR, sales).
Integrated Enterprise Systems – Enterprise-wide solutions affecting multiple functional areas.
Interorganizational Systems – Connect businesses with suppliers and customers.
Global Systems – Operate across national boundaries for multinational companies.
Enterprise Information Systems (EIS) Overview:
Definition – Large, modular, and integrated systems used across multiple functional areas.
Examples:
ERP (Enterprise Resource Planning) – Manages core business processes with integrated modules.
CRM (Customer Relationship Management) – Enhances customer interactions and relationships.
SCM (Supply Chain Management) – Optimizes supply chain operations and logistics.
WMS (Warehouse Management System) – Streamlines warehouse operations.
BI (Business Intelligence) – Analyzes data for decision-making.
EKM (Enterprise Knowledge Management) – Manages knowledge assets within the organization.
CMS (Content Management System) – Organizes digital content.
LMS (Learning Management System) – Facilitates training and education.
Perspectives of Enterprise Information Systems
1. Hierarchical Perspective – Tailors systems to organizational levels (operational, managerial, strategic).
2. Functional Perspective – Supports specific business functions (e.g., HR, Finance, Sales).
3. Process Perspective – Focuses on supporting end-to-end business processes.
Enterprise Resource Planning (ERP)
Definition – IS tools that integrate information flow within and between processes.
Key Features:
Process Perspective – Enables end-to-end integration of business functions.
Data Integration – Unified, centralized database for consistency.
Modular-Based – Different functional modules (e.g., Finance, HR, Supply Chain).
Customizable – Adaptable to business needs.
Customer Relationship Management (CRM)
Definition – Organization-wide strategy for managing interactions with customers.
Key Functions:
Multiple Interaction Channels – Unifies customer interactions (email, phone, web, etc.).
Customer Insights – Analyzes customer data for improved decision-making.
Lifecycle Management – Tracks customers from acquisition to retention.
Implementation Options:
On-Premise CRM – Installed locally, customizable but high cost.
Cloud-Based CRM (SaaS) – Hosted remotely, lower maintenance but standardized.
Supply Chain Management (SCM)
Definition – Manages the flow of goods, information, and money between suppliers and customers.
Key Components:
Supply Chain Flow – Streamlines processes from procurement to delivery.
Warehouse Automation & Robotics – Enhances efficiency through technology.
Warehouse Management Systems (WMS) – Optimizes inventory and logistics.
Human & Robotics Collaboration – Humans focus on strategic tasks, robots handle repetitive ones.
Session 5
Storing and Organizing Information
Databases and Database Management Systems (DBMS)
Database – An organized collection of data.
Relational Database –
Organizes data into connected, two-dimensional tables.
The dominant type of database in business applications.
Database Management System (DBMS) – Provides tools for creating, maintaining, and using databases efficiently.
Spreadsheets vs. Databases
Spreadsheets:
Prone to data duplication and inconsistencies.
Difficult to retrieve and search for data.
Poor data integrity leading to errors.
Good for analyzing and visually displaying data.
Databases:
Require planning and design but offer better data organization.
Better for storing large volumes of structured information.
More efficient and accurate than spreadsheets.
Multi-Tiered Architecture
Databases are core components of information systems.
They support business applications in storing, retrieving, and managing data.
Relational Databases
Record – A set of fields that belong to the same entity.
Field – A specific attribute or characteristic of an entity.
Primary Key – A unique identifier for each record in a table.
Composite Primary Key – A primary key consisting of multiple fields.
Foreign Key –
A field that references a primary key in another table.
Creates relationships between tables.
Structure – Organizes data into connected two-dimensional tables, making it a dominant business database model.
Database Relationships
One-to-Many (1:M) – One record in a table can relate to multiple records in another.
Many-to-Many (M:M) – Multiple records in one table relate to multiple records in another.
Database Diagrams & Entity-Relationship Diagrams (ERD)
Database Schema Diagrams – Used for larger databases to visualize structure.
Entity-Relationship Diagrams (ERD) – Graphical representations showing how tables relate.
Sessions 6 & 7
Knowledge Management (KM)
Definition: The process of generating, capturing, codifying, and transferring knowledge within an organization to create value.
Goal : Ensure that the right knowledge is available in a useful form to the right people at the right time for decision-making.
Benefits
Better problem-solving
Improved customer service
More effective product management
Increased innovation
More efficient processes
Higher intellectual capital
Better use of intellectual assets
Tacit vs. Explicit Knowledge
Explicit Knowledge – Easily expressed, shared, and documented (“Knowing that”).
Tacit Knowledge – Difficult to articulate, rooted in experiences, and requires direct interaction to transfer (“Know-how” / “savoir-faire”).
Types of Knowledge Resources
1. Experiential – Tacit; shared through experiences and interpersonal communication (skills, emotional intelligence).
2. Conceptual – Explicit; captured in language, symbols, and images (product designs, service concepts).
3. Systemic – Explicit; systemized and documented (patents, databases, manuals).
4. Routine – Tacit; embedded in organizational culture and daily operations (best practices, corporate habits).
Knowledge Management Cycle
1. Creation – Continuous transformation between tacit and explicit knowledge.
Socialization – Sharing tacit knowledge through direct interaction.
Externalization – Converting tacit knowledge into explicit knowledge.
Combination – Organizing and structuring explicit knowledge.
Internalization – Learning and embedding explicit knowledge as tacit.
2. Knowledge Capture & Codification
Capture techniques – Expert interviews, focus groups, lessons learned, task analysis.
Codification – Converting tacit and explicit knowledge into a structured, usable format.
Tools – Cognitive maps, decision tables, decision trees.
3. Knowledge Storage & Retrieval
Organization challenges – Knowledge exists in multiple formats (documents, audio, video, data).
Storage tools – Corporate directories, document storage systems, search engines.
4. Knowledge Transfer & Application
Transfer – Moves knowledge from storage to users through networks, training, corporate social tools.
Application – Ensures knowledge is available and useful to decision-makers.
Knowledge Management Technologies
1. Executive Information Systems (EIS) & Dashboards
Provide senior managers with high-level, summarized information.
Features: Graphical displays, drill-down capability, easy-to-use interface.
2. Expert Systems
Mimic human expert reasoning to provide guidance and solutions.
Used in narrow domains (e.g., technical troubleshooting).
3. Decision Support Systems (DSS)
Computer-based tools to help decision-makers handle semi-structured or unstructured problems.
DSS Categories:
Data-driven – Uses databases for insights.
Model-driven – Uses mathematical models.
Document-driven – Uses unstructured data (e.g., reports, emails).
Communication-driven – Uses collaboration tools (e.g., Groupware).
Business Intelligence (BI)
Definition – A set of applications, technologies, and processes for collecting, storing, analyzing, and accessing data to improve decision-making.
Data Storage & Processing
1. Data Warehouse – Centralized storage for structured, processed data used for analysis.
2. Data Mart – A subset of a data warehouse, designed for specific business units.
3. Data Sources & ETL (Extract, Transform, Load) – The process of collecting, converting, and storing data in a warehouse.
4. Data Mining – Identifying patterns and trends in large datasets.
Big Data
Definition – Massive volumes of structured and unstructured data beyond traditional processing capabilities.
Often measured in terabytes, petabytes, or larger.
The Three Vs of Big Data
1. Volume – Large quantities of data.
2. Velocity – Speed of data processing (batch, real-time, streaming).
3. Variety – Different formats (structured, unstructured, semi-structured).