Speech Analytics Overview Quiz

Ebenezer Management College

• Course Title: Business Intelligence
• Department of Computer Applications
• V Semester BCA
• Compiled by Prof Gomathi A, Associate Professor
• As per NEP Syllabus
• Bengaluru North University

Module-I: Business Intelligence

• Information Systems Support for Decision Making
  • Overview of decision-making processes in organizations
  • Types of decisions (strategic, tactical, operational) and their significance
  • Importance of timely and accurate information for effective decision making
  • Explanation of information systems and their role in organizations
  • Types of information systems (transaction processing systems, decision support systems, executive information systems)
• Decision Support Systems (DSS)
  • In-depth exploration of DSS and their role in supporting decision makers
  • Components of DSS (data management, model management, user interface)
  • Real-life examples of DSS applications
• Data Warehousing and Business Intelligence
  • Understanding data warehouses and their importance
  • Introduction to business intelligence tools for data analysis and reporting
• An Early Framework for Computerized Decision Support
  • Problem Definition
    • Identify and define the decision-making problem
    • Understanding the nature of decisions, frequency, and impact on the organization
  • Data Collection and Processing:
    • Methods for data collection and processing, data sources, formats, and procedures for data entry and storage
  • Model Development:
    • Models or algorithms for data analysis and decision support
    • Examples of statistical models, optimization models
• User Interface
  • Design of the interface for user interaction with the system
  • Interactivity and Feedback
• Knowledge Base
  • Relevant information and rules stored for decision-making
  • Decision-Making Logic
  • Rules for decision-making by the system
• Implementation and Integration
  • Hardware & software requirements
  • System integrations with existing processes and technologies
• User Training and Support
  • Training and support mechanisms for early adopters
• Evaluation and Improvement
  • Feedback loops to improve the systems, decision interfaces, and decision-making processes
• Security and Privacy
  • Early principles for ensuring security and privacy of data and decision-making processes

Module-II: Decision-Making Process

• Introduction and definitions
• The phases of the decision-making process
  • Intelligence Phase
  • Design Phase
  • Choice Phase
  • Implementation Phase
• Decision-support system capabilities
• Decision-support system classification
• Decision-support system components

Module-III: Neural Networks

• Basic concepts of neural networks
• Developing neural network-based systems
• Illuminating the black box of ANN with sensitivity
• Support vector machines
• A process-based approach to the use of SVM
• Nearest neighbor method for prediction
• Sentiment analysis overview
• Sentiment analysis applications
• Sentiment analysis process
• Sentiment analysis, speech analytics

Module-IV: Decision Support Systems

• Decision support systems modeling
• Structure of mathematical models for decision support
• Certainty, uncertainty, and risk
• Decision modeling with spreadsheets
• Mathematical programming optimization
• Decision analysis with decision tables and tree
• Multi-Criteria decision making with pairwise comparisons

Module-V: Artificial Intelligence

• Automated decision systems
  • Algorithms
  • Data
  • Models
  • Decision rules
  • Feedback mechanisms
• Applications of automated decision systems
• Challenges and considerations
  • Bias and fairness
  • Transparency
  • Ethical concerns
  • Accountability
  • Data privacy
  • Robustness and security
  • Human oversight
  • Continuous monitoring and evaluation
  • Legal and regulatory compliance
• Subfields of artificial intelligence
  • Machine Learning
  • Natural Language Processing
  • Computer Vision
  • Robotics

Test your knowledge on speech analytics with this insightful quiz. Explore key features such as compliance monitoring, sentiment analysis, and the role of Automatic Speech Recognition (ASR). Assess how these technologies shape organizational performance during customer interactions.