Data Collection Methods for Big Data Analytics: Principles, Techniques, and Challenges
Author: Dr. Anna Neya Kazanskaia
Publisher: NEYA Global Publishing
Article | NEYA Global Journal of Non-Profit Studies
Year: 2025
ORCID: https://orcid.org/0009-0009-5669-1676
DOI: https://doi.org/10.64357/neya-gjnps-hr-bg-dt-03
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About the Article
Effective data collection is foundational to big data analytics, shaping the accuracy, reliability, and ethical integrity of decision-making. This article examines internal and external data sources, structured, unstructured, and hybrid collection techniques, and mechanisms to ensure quality through cleaning, validation, and governance. Ethical safeguards—such as consent, anonymization, and compliance—are emphasized alongside strategies for low-resource settings, where infrastructure and literacy barriers require adaptive approaches. Case studies from healthcare, agriculture, and urban planning illustrate practical applications, while the discussion integrates theory, methodology, and context-specific challenges. The analysis highlights how organizations can adopt robust and responsible data collection practices as the cornerstone of effective big data analytics.
Key Topics
- Data collection principles and methods
- Internal and external data sources
- Data quality and governance
- Ethical and regulatory compliance
- Low-resource settings strategies
- Case studies in healthcare, agriculture, and urban planning
Suggested Citation
Kazanskaia, A. N. (2025). Data Collection Methods for Big Data Analytics: Principles, Techniques, and Challenges. NEYA Global Journal of Non-Profit Studies. Neya Global Publishing. https://doi.org/10.64357/neya-gjnps-hr-bg-dt-03
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