International Journal of Data Analysis Techniques and Strategies - Inderscience | 2024 Cite Score:1.6 | Q3

Cite Score and Journal Rank of International Journal of Data Analysis Techniques and Strategies

• About: International Journal of Data Analysis Techniques and Strategies (IJDATS) is a peer-reviewed academic journal that focuses on the development and application of data analysis techniques and strategies across various domains. The journal aims to advance the field of data analysis by publishing high-quality research and methodologies.
• Objective: The primary objective of the International Journal of Data Analysis Techniques and Strategies is to advance knowledge and practice in data analysis. The journal covers a wide range of topics including statistical analysis, machine learning, data mining, predictive modeling, and decision-making strategies. It provides a platform for researchers and practitioners to share their findings on new techniques, tools, and strategies for analyzing and interpreting complex data.
• Interdisciplinary Approach: The journal adopts an interdisciplinary approach by incorporating research from various fields where data analysis plays a critical role. This includes applications in business, finance, healthcare, social sciences, and engineering. By bridging multiple disciplines, the journal facilitates a comprehensive understanding of how data analysis methods can be applied to different types of data and problems. Contributions that offer novel insights or integrate techniques from multiple areas are especially encouraged.
• Impact and Significance: International Journal of Data Analysis Techniques and Strategies has a significant impact on both academic and professional communities involved in data analysis and its applications. The research published in the journal provides valuable contributions by presenting new methodologies, tools, and strategies that address current challenges in data analysis. It serves as a key resource for data scientists, analysts, and researchers who are engaged in developing and applying advanced data analysis techniques.

• Journal Home:  Journal Homepage

• Editor-in-Chief:  Prof. John Wang

• Scope: The International Journal of Data Analysis Techniques and Strategies focuses on advanced methods and strategies for analyzing and interpreting data. Its scope includes:
• 1. Data Analysis Techniques: Research on various techniques for analyzing data, including statistical methods, data mining, and machine learning algorithms.
• 2. Statistical Analysis: Studies on statistical methods and models for data analysis, including hypothesis testing, regression analysis, and multivariate analysis.
• 3. Machine Learning and AI: Exploration of machine learning algorithms and artificial intelligence techniques for data analysis, including supervised and unsupervised learning, neural networks, and deep learning.
• 4. Data Mining: Research on techniques for discovering patterns and extracting useful information from large datasets, including clustering, association rule mining, and anomaly detection.
• 5. Big Data Analytics: Studies on methods and technologies for analyzing large and complex datasets, including distributed computing, cloud computing, and big data frameworks.
• 6. Predictive Analytics: Research on techniques for making predictions based on data, including forecasting methods, predictive modeling, and risk assessment.
• 7. Data Visualization: Exploration of methods and tools for visualizing data to aid in understanding and interpreting complex datasets, including graphical representations and interactive dashboards.
• 8. Data Quality and Management: Studies on ensuring data quality, data cleansing, and data management practices to support effective data analysis.
• 9. Time Series Analysis: Research on methods for analyzing time series data, including trend analysis, seasonal decomposition, and forecasting.
• 10. Computational Techniques: Exploration of computational methods and algorithms used in data analysis, including optimization techniques and numerical methods.
• 11. Statistical Computing: Studies on computational tools and software for statistical analysis, including programming languages, statistical packages, and data analysis platforms.
• 12. Data Integration and Fusion: Research on methods for integrating and fusing data from multiple sources to provide a comprehensive analysis.
• 13. Ethical and Privacy Considerations: Exploration of ethical issues and privacy concerns related to data analysis, including data protection, consent, and responsible data use.
• 14. Applications of Data Analysis: Studies on the application of data analysis techniques in various domains such as healthcare, finance, marketing, and social sciences.
• Latest Research Topics for PhD in Machine Learning
• Latest Research Topics for PhD in Data Mining

• Print ISSN:  1755-8050

  Electronic ISSN:  1755-8069

• Abstracting and Indexing:  SCOPUS

• Imapct Factor :  

• Subject Area and Category:   Computer Science, Information Systems, Decision Sciences, Information Systems and Management, Mathematics, Applied Mathematics

• Publication Frequency:  

• H Index:  20

• Best Quartile:

  Q1:  

  Q2:  

  Q3:  Applied Mathematics

  Q4:  

• Cite Score:  1.6

• SNIP:  0.788

• Journal Rank(SJR):  0.284

• Latest Articles:   Latest Articles in International Journal of Data Analysis Techniques and Strategies

• Guidelines for Authors: International Journal of Data Analysis Techniques and Strategies Author Guidelines

• Paper Submissions: Paper Submissions in International Journal of Data Analysis Techniques and Strategies

• Publisher:  Inderscience Enterprises Ltd

  Country:  United Kingdom

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