International Journal of Data Warehousing

The International Journal of Data Warehousing is a peer-reviewed journal. International Journal of Data Warehousing (IJDW) aims to publish and disseminate knowledge on an international basis in the areas of data warehousing and data mining. It is published with the purpose of providing a forum for state-of-the-art developments and research, as well as current innovative activities in data warehousing and mining. In contrast to other journals, this journal focuses on the integration between the fields of data warehousing and data mining, with emphasize on the applicability to real world problems. The journal is targeted at both academic researchers and practicing IT professionals.

The journal focuses on articles on advances in applications of Data Warehousing, Data models, Data structures, Design, Data warehousing process, Online analytical process, Tools and languages, Data mart, Data Mining, Data mining methods, Algorithms, Mining databases, Knowledge discovery process, Tools and languages, intelligent techniques used for business modeling, including all areas of data visualisation, Business Intelligence, Biomedical literature data mining, Biological data curation, Data extraction and reporting, OLAP, Data cleaning and pre-processing, Decision analysis, Causal modeling, Reasoning under uncertainty, Uncertainty and noise in data,  Business intelligence cycle, model specification and estimation, Web technology, mining and agents, Intelligent Techniques, Fuzzy, neural, and evolutionary approaches, Genetic algorithms, Machine learning, Expert systems, Hybrid systems, Bayesian inference, bootstrap and randomization, Data Analysis, Exploratory and automated data analysis, Knowledge-based analysis, Statistical pattern recognition, Classification, projection, regression, optimization clustering, High performance bio-computing, Information extraction and retrieval, Multivariate data visualisation data pre-processing, data engineering, data mining techniques, tools and applications, neurocomputing, evolutionary computing, fuzzy techniques, expert systems, knowledge filtering, and post-processing and developments in these fields have direct implications on key issues related to data warehousing.

International Journal of Data Warehousing (IJDW) is an essential journal for all academic and industrial researchers who want expert knowledge on all major advances in data warehousing.

The journal aims to provide the most complete and reliable source of information on current developments in the field. The emphasis will be on publishing quality articles rapidly and openly available to researchers worldwide. All published articles will be deposited immediately upon publication in at least one widely and internationally recognized open access repository. Moreover, it is providing the maximum exposure to the articles.

The journal will be essential reading for scientists and researchers who wish to keep abreast of the latest developments in the field. The publishers are confident of the journal’s rapid success.

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