Download presentation

Modern automation systems for commercial banking can support not only business processes but also analytical data processing. The heterogeneity of systems in the parameter “developer” is now natural, and different data models are used to organize the information space. This trend appears in the creation of analytical subsystems where the user needs so-called slices of data (not detailed data). In this case on-line analytical processing (OLAP) is supported by multidimensional databases and relational and object-oriented databases are used for data mining.

The problems of heterogeneous information space arise in case you need to transform different data models within a single business process in real time. However, a successful information system structure can effectively solve analytical processing problems.

One of the main problems of commercial banking is cash center’s (CC) resource planning (mainly cash).

This paper proposes analytical module to solve the cash planning problems. The module is built on both relational and multidimensional databases.

Ivan Kaurov

Ivan Kaurov

Ivan V. Kaurov is now postgraduate student at St.Petersburg State Polytechnic University. He got his Master’s degree in 2008 at the chair of information and control systems of the department of technical cybernetics. He works for “Business consultations, St.Petersburg” LLC since 2008 where he is involved in development of accounting systems both for banking and for retail stores. Nowadays Ivan is studying and developing analytical and intelligent systems.

Sergey Ustinov

Dmitry Drobintsev