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Tag: Data Aggregation

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Tanu Singh | Data Warehouse | Best Researcher Award

Posted on 25/03/2025 by ScienceFather

Dr. Tanu Singh | Data Warehouse | Best Researcher Award

UPES, Dehradun, India

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๐ŸŽ“ Early Academic Pursuits

Dr. Tanu Singhโ€™s academic journey is a testament to her passion for Computer Science & Engineering ๐Ÿ–ฅ๏ธ. She began her higher education with a Bachelor of Technology (B.Tech) in Information Technology from I.K. Gujral Punjab Technical University, completing it in 2011 with an impressive 81%. Her enthusiasm for research and technical innovation led her to pursue a Master of Technology (M.Tech) in Computer Science & Engineering at the same university, which she successfully completed in 2014, securing 77%.

Eager to deepen her expertise, she embarked on a rigorous Ph.D. in Computer Science & Engineering at Guru Gobind Singh Indraprastha University, New Delhi ๐ŸŽ“. Her thesis, titled โ€œValidation of Metrics for Quality Assessment of Requirements Model for Data Warehouseโ€, focused on Requirements Engineering, Data Warehousing, and Machine Learning ๐Ÿง . Under the guidance of Dr. Manoj Kumar, she conducted groundbreaking research that contributed significantly to the field.

๐Ÿ‘ฉโ€๐Ÿซ Professional Endeavors

With a solid foundation in academia, Dr. Tanu Singh transitioned into the role of an Assistant Professor (Senior Scale) at the School of Computer Science, UPES-Bidholi Campus, Dehradun ๐Ÿ“. Her teaching methodology is a blend of practical application, research-driven insights, and interactive learning. Over the years, she has mentored numerous students, helping them build expertise in fields like Data Warehousing, Machine Learning, and Requirements Engineering.

Apart from teaching, she has played an active role in academic administration, curriculum development, and research collaborations ๐Ÿ“š. Her ability to bridge theory with real-world applications has made her a respected educator in the field.

๐Ÿ”ฌ Contributions and Research Focus

Dr. Tanu Singhโ€™s research interests lie at the intersection of Requirements Engineering, Data Warehousing, and Machine Learning ๐Ÿค–๐Ÿ“Š. Her Ph.D. research introduced innovative quality assessment metrics that enhanced the efficiency and reliability of Data Warehouse Requirements Models. This work is crucial in ensuring that data-driven decision-making systems are more accurate, scalable, and optimized.

Her contributions include:

  • ๐Ÿ“Œ Development of validation metrics to assess the quality of Data Warehouse models

  • ๐Ÿ“Œ Application of Machine Learning techniques to improve requirements engineering

  • ๐Ÿ“Œ Bridging the gap between theory and real-world applications through her research

Her work has been widely acknowledged and has laid the foundation for future advancements in the field of Data Warehousing ๐Ÿ—๏ธ.

๐Ÿ† Accolades and Recognition

Dr. Tanu Singhโ€™s relentless dedication to research and education has earned her several accolades, including:

  • ๐Ÿ… Recognition for her high-impact Ph.D. research in Requirements Engineering

  • ๐Ÿ… Acknowledgment from Guru Gobind Singh Indraprastha University for her contributions to academic research

  • ๐Ÿ… Consistently high student feedback ratings for her engaging and insightful teaching methods

Her work has been presented at national and international conferences, where she has received praise for her innovative approach to problem-solving.

๐ŸŒ Impact and Influence

Dr. Tanu Singhโ€™s influence extends beyond research and teaching ๐Ÿ“–. She actively participates in:

  • ๐Ÿ”น Workshops and Seminars to spread knowledge about emerging trends in Data Science and Machine Learning

  • ๐Ÿ”น Mentoring students for research projects, ensuring they develop practical expertise

  • ๐Ÿ”น Collaboration with industry experts to align academic research with real-world applications

Her efforts have helped students and professionals grasp complex technical concepts with ease, making her a sought-after academic mentor.

๐Ÿš€ Legacy and Future Contributions

Looking ahead, Dr. Tanu Singh aims to:
โœ… Expand her research in Machine Learning-driven Requirements Engineering ๐Ÿง ๐Ÿ“Š
โœ… Publish high-impact papers in top-tier journals ๐Ÿ“œ
โœ… Develop innovative teaching strategies to empower the next generation of Computer Science professionals ๐Ÿ’ก
โœ… Collaborate with global researchers to advance Data Warehousing technologies ๐ŸŒŽ

Her passion for knowledge, research, and education ensures that she will continue making valuable contributions to the field, leaving a lasting legacy in Computer Science & Engineering.

Citations

A total of 14 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

  • Citations         14
  • h-index           08
  • i10-index        02

Notable Publications 

  • A Novel Metric for Assessing Structural Complexity of Data Warehouse Requirements Models

    • Authors: T Singh, V Patidar, M Singh

    • Journal: Expert Systems with Applications

    • Year: 2024.

  • Explainable AI for Education: Recent Trends and Challenges

    • Authors: T Singh, S Dutta, S Vyas, ร Rocha

    • Journal: Springer Nature Switzerland, Imprint: Springer

    • Year: 2024.

  • Employ Metrics in the Data Warehouseโ€™s Requirements Model for Hospitals

    • Authors: T Singh, B Kaushik

    • Journal: Handbook on Augmenting Telehealth Services

    • Year: 2024.

  • A Survey on SCADAโ€™s Security, Concerns and Attacks

    • Authors: TJS Singh, JI Sheeba, SP Devaneyan

    • Journal: International Conference on Advancements in Smart Computing and Information

    • Year: 2023.

  • Schema Understandability: A Comprehensive Empirical Study of Requirements Metrics

    • Authors: T Singh, V Patidar, M Singh, ร Rocha

    • Journal: Information

    • Year: 2025.

Posted in: BiographyTagged: Big Data, business intelligence, Cloud Data Warehousing, Data Aggregation, data governance, data integration, Data Lake, Data Mart, Data Mining, data modeling, data pipelines, data quality, data storage, Data Transformation, Data Warehouse, Data Warehouse Architecture, Data Warehouse Automation, Data Warehouse Best Practices, Data Warehouse Design, Data Warehouse Management, Data Warehouse Optimization, Data Warehouse Performance, Data Warehouse Security, Data Warehouse Testing, Data Warehouse Tools, data warehousing, Decision Support Systems, Dimension Table, Dimensional Modeling, Enterprise Data Warehousing, ETL (Extract, Fact Table, Load), Metadata Management, Multi-Dimensional Data, OLAP (Online Analytical Processing), Real-Time Data Warehousing, Snowflake Schema, SQL for Data Warehousing, Star Schema, Transform

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