By the end of this training, participants will be able to:

• Understand the role of data collection in research and decision-making
• Differentiate between qualitative and quantitative data collection methods
• Identify appropriate data sources for different objectives
• Understand survey design, interviews, and observational techniques (conceptually)
• Evaluate data quality, reliability, and validity
• Recognize ethical considerations in data collection
• Understand challenges and limitations in collecting data

Gain awareness of modern trends in digital data collection 

• Researchers and analysts
• Business and market analysts
• Government and policy professionals
• Students and academic researchers
• Monitoring and evaluation (M&E) professionals
• Anyone involved in data-driven decision-making

Day 1: Introduction to Data Collection

• What is data collection?
• Types of data: qualitative vs quantitative
• Primary vs secondary data sources
• Data collection in different fields (business, government, research)
• Overview of the data collection process
• Linking objectives to data needs
• Common challenges in data collection

Day 2: Quantitative Data Collection Methods

• Structured data collection approaches
• Surveys and questionnaires (conceptual design principles)
• Sampling techniques (random, stratified, convenience, etc.)
• Measurement scales (nominal, ordinal, interval, ratio)
• Data reliability and validity
• Common errors and biases in quantitative data
• Introduction to digital survey tools (conceptual, e.g., Google Forms concepts)

Day 3: Qualitative Data Collection Methods

• Characteristics of qualitative data
• Interviews (structured, semi-structured, unstructured)
• Focus groups and group discussions
• Observation techniques (participant vs non-participant)
• Case studies and field research
• Recording and documenting qualitative data
• Strengths and limitations of qualitative approaches

Day 4: Data Quality, Ethics & Management

• Data accuracy, consistency, and completeness
• Data validation and verification concepts
• Ethical considerations in data collection
• Consent and privacy
• Confidentiality and data protection
• Bias and how to minimize it
• Data storage and management principles
• Introduction to data governance concepts

Day 5: Advanced Topics & Modern Trends

• Mixed-methods approaches (qualitative + quantitative)
• Big data and automated data collection
• Digital and online data sources (social media, sensors, etc.)
• Challenges in modern data collection (data overload, misinformation)
• Evaluating and selecting appropriate techniques
• Case study discussions (research and real-world scenarios)
• Course recap and open discussion

BTS attendance certificate will be issued to all attendees completing minimum of 80% of the total course duration.

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