OLAP and NoSQL: Happily Ever After
Abstract. NoSQL databases are preferred to relational ones for storing heterogeneous data with variable schemas and structural forms. However, their schemaless nature adds complexity to analytical applications, in which a single OLAP analysis often involves large sets of data with different schemas. In this tutorial we describe the main approaches to enable OLAP on NoSQL data. We start from schema-on-read approaches, where data are left unchanged in their structure until they are accessed by the user, so they are put into multidimensional form at query time. Specifically, we show how this enables a form of approximated OLAP that embraces and exploits the inherent variety of schemaless data. Then we move to schema-on-write approaches, where a fixed multidimensional structure is forced onto data, which are loaded into a data warehouse to be then queried. In particular, we introduce multi-model data warehouses as a way to store data in multidimensional form and, at the same time, let each piece of data be natively represented through the most appropriate NoSQL model.
Stefano Rizzi received his Ph.D. in 1996 from the University of Bologna, Italy. Since 2005 he is Full Professor at the University of Bologna. He has published more than 150 papers in international refereed journals and conferences mainly in the fields of data warehousing, business intelligence, and pattern recognition, and a research book on data warehouse design. He is member of the steering committee of DOLAP. His current research interests include data warehouse design and business intelligence, in particular OLAP on NoSQL data, social business intelligence, and analysis services for big data.