Data Modeling for Big Data Analytics
A special issue of Informatics (ISSN 2227-9709).
Deadline for manuscript submissions: closed (31 December 2018) | Viewed by 15812
Special Issue Editors
Interests: big data; big data analytics; NoSQL databases; data warehouse; design process; data mining; analytics; social business intelligence; opinion mining; preference queries; what-if analysis; precision farming; ontologies; machine learning; trajectory data analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Business intelligence (BI) applications are data-intensive; thus, data modeling is a key aspect to ensure their effectiveness and efficiency. At the conceptual level, data modeling provides a high level of abstraction in describing the structure and features of the information to be delivered in an implementation-independent way. At the logical and physical levels, it enables data structures to be specifically fine-tuned to achieve good performances on the target data model. Since the 1990s, data modeling for BI has mainly meant multidimensional modeling, which has been a key to access the benefits of OLAP [DM1] querying in data warehouses. Nowadays, the increase in analytics and big data technologies asks for a review and extension of the classical multidimensional paradigm and paves the way to new solutions tailored for the emerging user needs and for the specific technological features of big data platforms. In this context, we seek for original submissions that contribute novel approaches, solutions, methods, languages, and applications on the following topics:
- Data modeling in the context of conceptual design of data warehouses, analytics, and business intelligence applications, in presence of big data sources
- Data modeling in the context of logical design of data warehouses, analytics, and business intelligence applications, when the target platform is a big data one
- Design methodologies related to the above mentioned data models
- Techniques for efficiently querying and accessing the above mentioned data models
Prof. Stefano Rizzi
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Informatics is an international peer-reviewed open access quarterly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- Foundations and Concept Formalization
- Domain-Specific Models and Methods
- Methodologies and Tools
- Quality and Metrics
- Evolution
- Metadata and Applications
- Spatio-Temporal Aspects
- Modeling of Stream and Sensor Data
- Empirical Studies
- NoSQL and NewSQL Databases
- Big Data Analytics
