Abstract
A significant expansion of Big Data and NoSQL databases made it necessary to develop new architectures for Business Intelligence systems based on data organized in a non-relational way. There are many novel solutions combining Big Data technologies with Data Warehousing. However, the proposed solutions are often not sufficient enough to meet the increasing business demands, such as low data latency while still maintaining high functionality, efficiency and reliability of Data Warehouses. In this paper we propose DUABI - the BI architecture that enables both traditional analytics over OLAP Cube as well as near real-time analytics over the data stored in the NoSQL database. The presented architecture leverages features of NoSQL databases for scalability and fault-tolerance with the use of mechanisms like sharding and replication.
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Czajkowski, B., Zawadzka, T. (2017). DUABI - Business Intelligence Architecture for Dual Perspective Analytics. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds) Beyond Databases, Architectures and Structures. Towards Efficient Solutions for Data Analysis and Knowledge Representation. BDAS 2017. Communications in Computer and Information Science, vol 716. Springer, Cham. https://doi.org/10.1007/978-3-319-58274-0_41
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DOI: https://doi.org/10.1007/978-3-319-58274-0_41
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