Original scientific paper
https://doi.org/10.2498/cit.1002263
Design of a Unified Data with Business Rules Storage Model for OLTP and OLAP Systems
Stephen Opoku-Anokye
; Informatics Research Centre, Henley Business School, University of Reading, United Kingdom
Yinshan Tang
; Informatics Research Centre, Henley Business School, University of Reading, United Kingdom
Abstract
This paper reviews the literature concerning the practice of using Online Analytical Processing (OLAP) systems to recall information stored by Online Transactional Processing (OLTP) systems. Such a review provides a basis for discussion on the need for the information that are recalled through OLAP systems to maintain the contexts of transactions with the data captured by the respective OLTP system. The paper observes an industry trend involving the use of OLTP systems to process information into data, which are then stored in databases without the business rules that were used to process information and data stored in OLTP databases without associated business rules. This includes the necessitation of a practice, whereby sets of business rules are used to extract, cleanse, transform and load data from disparate OLTP systems into OLAP databases to support the requirements for complex reporting and analytics. These sets of business rules are usually not the same as business rules used to capture data in particular OLTP systems. The paper argues that differences between the business rules used to interpret these same data sets risk gaps in semantics between information captured by OLTP systems and information recalled through OLAP systems. The literature concerning the modeling of business transaction information as facts with context as part of the modelling of information systems was reviewed to identify design trends that are contributing to the design quality of OLTP and OLAP systems. The paper then argues that the quality of OLTP and OLAP systems design has a critical dependency on the capture of facts with associated context, encoding facts with contexts into data with business rules, storage and sourcing of data with business rules, decoding data with business rules into the facts with the context and recall of facts with associated contexts. The paper proposes UBIRQ, a design model to aid the co-design of data with business rules storage for OLTP and OLAP purposes. The proposed design model provides an opportunity for the implementation and use of multi-purpose databases and business rules stores for OLTP and OLAP systems. Such implementations would enable the use of OLTP systems to record and store data with executions of business rules, which will allow for the use of OLTP and OLAP systems to query data with business rules used to capture the data, thereby ensuring that information recalled via OLAP systems preserves the contexts of transactions as per the data captured by the respective OLTP system.
Keywords
OLTP systems design; OLAP systems design; facts with contexts modelling; data with business rules modelling
Hrčak ID:
129374
URI
Publication date:
10.11.2014.
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