To explain the role of relational databases in OLAP
, multidimensional data are explained.
Based on the problems above, it is quite natural that the Top-K recommendation can be introduced in OLAP
sessions since this approach can find the latent valuable target which can well raise the effectiveness of recommendations [13-14].
queries and reports, and the decisions and transactions they affect, are always based on the latest committed data.
A multi-dimensional model of a data warehouse star schema, snowflake schema, fact constellations and data cube consists of dimensions and measures, OLAP
operations includes drilling, rolling, slicing, dicing and pivoting OLAP
servers such as ROLAP, MOLAP, HOLAP.
technology can pre-create data model, to provide sufficient audit data in advance for auditors, thus saving the data collection time in audit procedures and greatly improving the work efficiency of audit.
Identification of Aggregation Functions: The OLAP
operations include rollup, drill-down, slicing and dicing and pivoting.
is a computer-based technique which enables users to interactively analyze business data.
The need of OLAP
as a part of flexible and efficient SCM is obvious.
provides a multidimensional view of data that allows patterns to be discerned in even the largest datasets that remain invisible even to the most expert user of spreadsheets.
the first thing that comes to the mind is building of OLAP
cubes to facilitate business intelligence.
* drill-down and drill-through OLAP
capabilities for users to further investigate results;