Analytics Tools and Techniques in Big Data: Descriptive, Predictive, and Prescriptive Approaches
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-04
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About the Article
Big data analytics relies on diverse tools and techniques to transform vast datasets into actionable insights. This article explores descriptive, predictive, and prescriptive analytics as complementary frameworks for organizational decision-making. It examines technologies such as Hadoop, Spark, SQL, and NoSQL databases, alongside visualization platforms like Tableau and Power BI, and programming environments including Python and R. Case studies from Uber, Facebook, healthcare, retail, and aviation illustrate how analytics informs pricing, efficiency, customer engagement, and risk management. Challenges of scalability, data quality, and ethics are critically assessed, with strategies for open-source adoption, workforce training, and project alignment to organizational goals. Positioned at the intersection of technology, methodology, and governance, the discussion offers both conceptual clarity and practical guidance for organizations seeking to expand analytics capacity, particularly in resource-constrained settings.
Key Topics
- Big data analytics frameworks
- Descriptive, predictive, prescriptive approaches
- Tools: Hadoop, Spark, SQL, NoSQL
- Visualization and open-source platforms
- Case studies across industries
- Scalability, ethics, and best practices
Suggested Citation
Kazanskaia, A. N. (2025). Analytics Tools and Techniques in Big Data: Descriptive, Predictive, and Prescriptive Approaches. NEYA Global Journal of Non-Profit Studies. Neya Global Publishing. https://doi.org/10.64357/neya-gjnps-hr-bg-dt-04
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