: Over the years, DataWarehousing has gone through a number of evolutions from a relatively simple reporting database to sophisticated analytical applications such as analyzing cus...
In classical data warehouses (DWH), classification of values takes place in a sharp manner, because of this true values cannot be measured and smooth transition between classes do...
Large-scale data analysis has become increasingly important for many enterprises. Recently, a new distributed computing paradigm, called MapReduce, and its open source implementat...
Multidimensional models are at the core of data warehouse systems, since they allow decision makers to early define the relevant information and queries that are required to satis...
The emergence of new higher education institutions has created the competition in higher education market, and data warehouse can be used as an effective technology tools for incr...
The duplicate elimination problem of detecting multiple tuples, which describe the same real world entity, is an important data cleaning problem. Previous domain independent solut...
A data warehouse collects and maintains a large amount of data from several distributed and heterogeneous data sources. Often the data is stored in the form of materialized views ...
We are developing a vendor-independent archive and on top of that a data warehouse for mass spectrometry metabolomics data. The archive schema resembles the communitydeveloped obj...
: Integration of multiple data sources is becoming increasingly important for enterprises that cooperate closely with their partners for e-commerce. OLAP enables analysts and decis...
Data warehouse systems service larger and larger sets of data. Effective data indexing is not sufficient, because one system node is unable to store such amount ofquickly flowing ...
Marcin Gorawski, Michal Gorawski, Slawomir Bankows...