Big Data Analytics Adoption Framework is a B.Tech project topic for Information Technology. It gives students a clear starting point for research, implementation planning, and documentation.
Big Data Analytics Adoption Framework Project Details
| Abstract |
This project explores the structured adoption of Big Data Analytics (BDA) within organizational workflows, utilizing a modified Cross-Industry Standard Process for Data Mining (CRISP-DM) framework. The research systematically decomposes standard analytical processes into actionable sub-processes while integrating critical success factors (CSFs) essential for deployment. To validate this conceptual framework, a comprehensive case study is analyzed, focusing on an agricultural BDA enterprise that assists large-scale farming operations through data-driven decision-making. The investigation identifies key operational determinants, including project planning, cost estimation, adoption strategy, business problem identification, team formation, data management, training, and change management. Furthermore, the framework incorporates post-implementation factors such as system maintenance, continuous evaluation of business objectives, and holistic
project management. This implementation support resource provides structured guidance for IT students to model, simulate, and evaluate BDA adoption strategies. By mapping these theoretical phases to practical software engineering workflows, the project offers a systematic approach to analyzing organizational readiness, data pipeline integration, and lifecycle management in modern data analytics initiatives.
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| Reference Paper |
Big Data Analytics Adoption Framework and its Verification Using a Case Study |
| Domain |
Information Technology |
| Sub-Domain |
Data Analytics |
| PDF Download |
Download / View PDF |
| Get Help |
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