Design of a unified data with business rules storage model for OLTP and OLAP systems

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. Literature concerning the modeling of business transaction information as facts with context as part of the modelling of information systems were 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 the 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 information recalled via OLAP systems preserves the contexts of transactions as per the data captured by the respective OLTP system

Active databases, business rules and reactive agents - what is the connection?

These three technologies were and still are mainly treated separately. Since not much work has been carried out in defining and combining them together, we are going to present what has been done and put accent on what could be done. Namely, they rely upon similar paradigms and concepts, as will be shown later on, and can be treated as complementary technologies. In this paper we will show that reactive agents react according to some set of business rules and active databases can be used as a suitable means for implementing business rules and in those way reactive agents as well. Since reactive agents have been well defined, recent improvements in the fields of active databases technology and especially business rules provide the reason to consider the benefits to be achieved from combining these fields

Active databases, business rules and reactive agents - what is the connection?

These three technologies were and still are mainly treated separately. Since not much work has been carried out in defining and combining them together, we are going to present what has been done and put accent on what could be done. Namely, they rely upon similar paradigms and concepts, as will be shown later on, and can be treated as complementary technologies. In this paper we will show that reactive agents react according to some set of business rules and active databases can be used as a suitable means for implementing business rules and in those way reactive agents as well. Since reactive agents have been well defined, recent improvements in the fields of active databases technology and especially business rules provide the reason to consider the benefits to be achieved from combining these fields

Database Vs Data Warehouse

Data warehouse technology includes a set of concepts and methods that offer the users useful information for decision making. The necessity to build a data warehouse arises from the necessity to improve the quality of information in the organization. The date proceeding from different sources, having a variety of forms - both structured and unstructured, are filtered according to business rules and are integrated in a single large data collection. Using informatics solutions, managers have understood that data stored in operational systems - including databases, are an informational gold mine that must be exploited. Data warehouses have been developed to answer the increasing demands for complex analysis, which could not be properly achieved with operational databases. The present paper emphasizes some of the criteria that information application developers can use in order to choose between a database solution or a data warehouse one.data warehouse, database, database management systems, information systems, data organisation in externe memory, business intelligence

An Architecture to infer Business Rules from Event Condition Action Rules implemented in the Persistence Layer

The business rules that govern the behaviour of a business process can be hardcoded in different ways in a software application. The modernization or improvement of these applications to a process-oriented perspective implies typically the modification of the business rules. Frequently, legacy systems are not well-documented, and almost always, the documentation they have is not updated. As a consequence many times is necessary the analysis of source code and databases structures to be transformed into a business language more understandable by the business experts involved in the modernization process. Database triggers are one of the artefacts in which business rules are hardcoded. We focus on this kind of artefacts, having in mind to avoid the manual analysis of the triggers by a database expert, and bringing it closer to business experts. To get this aim we need to discover business rules that are hardcoded in triggers, and translate it into vocabularies that are commonly used by business experts. In this paper we propose an ADM-based architecture to discover business rules and rewrite then into a language that can be understood by the business experts.Ministerio de Ciencia y Tecnología TIN2009-13714Ministerio de Ciencia y Tecnología TIN2010-20057-C03-02Ministerio de Ciencia y Tecnología TIN2010-21744-C02-

Fault diagnosis in databases for business processes

Business processes involve data that can be modified or updated by various activities. These data must satisfy the business rules associated to the process. As the information treated in a business process tends to be extensive, data are normally stored in a relational database, and hence the database has to be analyzed to determine whether the business rules are satisfied and what values are incorrect. This paper proposes the use of model-based diagnosis in the business processes scenario. This scenario combines business processes, business rules, relational databases and where the faults are the instances of the variables introduced by the users. These considerations make it necessary to introduce a new way for representing the model, and the design of new algorithms to solve it. This model provides a means for the detection of incorrect tuples of different tables of the database by avoiding the analysis of the full database. Furthermore, in order to manage the current business rules, the use of a constraint paradigm is proposed and by using Max- CSPs to isolate incorrect values.Junta de Andalucía P08-TIC-04095Ministerio de Ciencia y Tecnología TIN2009-1371

Using Neural Networks for Pattern Association for the Online Purchase of Products

Abstract: Today, a huge percentage of all the business transactions that take place in the domain of e-commerce are dominated by online shopping after the virtual market conceptualization of the business. This paper focuses on how pattern association rules may be obtained from the dynamic databases generated during purchases in an e-Store to maximize the profit of the marketer. In this paper, ANN has been used as a tool for generating pattern association rules during online purchases of products to aid the cross-selling of products. For getting the rules, a methodology using artificial neural networks has been adapted for usage using an extended Delta rule for initial training of the network and a hetero-associative neural network for generating and storing the associative rules. Also, a methodology has been proposed to filter out all rules which do not add economic value to the firm and then select that rule which will meet the profit maximization objective of the marketer

Large-Scale Legal Reasoning with Rules and Databases

Traditionally, computational knowledge representation and reasoning focused its attention on rich domains such as the law. The main underlying assumption of traditional legal knowledge representation and reasoning is that knowledge and data are both available in main memory. However, in the era of big data, where large amounts of data are generated daily, an increasing rangeof scientific disciplines, as well as business and human activities, are becoming data-driven. This chapter summarises existing research on legal representation and reasoning in order to uncover technical challenges associated both with the integration of rules and databases and with the main concepts of the big data landscape. We expect these challenges lead naturally to future research directions towards achieving large scale legal reasoning with rules and databases

Inconsistency-tolerant business rules in distributed information systems

The final publication is available at Springer via http://10.1007/978-3-642-41033-8_41Business rules enhance the integrity of information systems. However, their maintenance does not scale up easily to distributed systems with concurrent transactions. To a large extent, that is due to two problematic exigencies: the postulates of total and isolated business rule satisfaction. For overcoming these problems, we outline a measure-based inconsistency-tolerant approach to business rules maintenance.Supported by ERDF/FEDER and MEC grants TIN2009-14460-C03, TIN2010-17139, TIN2012-37719-C03-01.Decker, H.; Muñoz Escoí, FD. (2013). Inconsistency-tolerant business rules in distributed information systems. En On the Move to Meaningful Internet Systems: OTM 2013 Workshops. Springer Verlag (Germany). 8186:322-331. https://doi.org/10.1007/978-3-642-41033-8_41S3223318186Abiteboul, S., Hull, R., Vianu, V.: Foundations of Databases. Addison-Wesley (1995)Berenson, H., Bernstein, P., Gray, J., Melton, J., O’Neil, E., O’Neil, P.: A critique of ANSI SQL isolation levels. In: Proc. SIGMOD 1995, pp. 1–10. ACM Press (1995)Bernstein, P., Hadzilacos, V., Goodman, N.: Concurrency Control and Recovery in Database Systems. Addison-Wesley (1987)Butleris, R., Kapocius, K.: The Business Rules Repository for Information Systems Design. In: Proc. 6th ADBIS, vol. 2, pp. 64–77. Slovak Univ. of Technology, Bratislava (2002)Davis, C.T.: Data Processing sphere of control. IBM Systems Journal 17(2), 179–198 (1978)Decker, H.: Partial Repairs that Tolerante Inconsistency. In: Eder, J., Bielikova, M., Tjoa, A.M. (eds.) ADBIS 2011. LNCS, vol. 6909, pp. 389–400. Springer, Heidelberg (2011)Decker, H.: Causes of the violation of integrity constraints for supporting the quality of databases. In: Murgante, B., Gervasi, O., Iglesias, A., Taniar, D., Apduhan, B.O. (eds.) ICCSA 2011, Part V. LNCS, vol. 6786, pp. 283–292. Springer, Heidelberg (2011)Decker, H.: New measures for maintaining the quality of databases. In: Murgante, B., Gervasi, O., Misra, S., Nedjah, N., Rocha, A.M.A.C., Taniar, D., Apduhan, B.O. (eds.) ICCSA 2012, Part IV. LNCS, vol. 7336, pp. 170–185. Springer, Heidelberg (2012)Decker, H.: Controlling the Consistency of the Evolution of Database Systems. In: Proc. 24th ICSSEA, Paris (2012)Decker, H., Martinenghi, D.: Inconsistency-tolerant Integrity Checking. IEEE Transactions on Knowledge and Data Engineering 23(2), 218–234 (2011)Decker, H., Muñoz-Escoí, F.D.: Revisiting and Improving a Result on Integrity Preservation by Concurrent Transactions. In: Meersman, R., Dillon, T., Herrero, P. (eds.) OTM 2010 Workshops. LNCS, vol. 6428, pp. 297–306. Springer, Heidelberg (2010)Eswaran, K., Gray, J., Lorie, R., Traiger, I.: The Notions of Consistency and Predicate Locks in a Database System. CACM 19(11), 624–633 (1976)Gilbert, S., Lynch, N.: Brewer’s Conjecture and the feasibility of Consistent, Available, Partition-tolerant Web Services. ACM SIGACT News 33(2), 51–59 (2002)Ibrahim, H.: Checking Integrity Constraints - How it Differs in Centralized, Distributed and Parallel Databases. In: Proc. 17th DEXA Workshops, pp. 563–568. IEEE (2006)Lynch, N., Blaustein, B., Siegel, M.: Correctness Conditions for Highly Available Replicated Databases. In: Proc. 5th PODC, pp. 11–28. ACM Press (1986)Martinenghi, D., Christiansen, H.: Transaction Management with Integrity Checking. In: Andersen, K.V., Debenham, J., Wagner, R. (eds.) DEXA 2005. LNCS, vol. 3588, pp. 606–615. Springer, Heidelberg (2005)Christiansen, H., Decker, H.: Integrity checking and maintenance in relational and deductive databases and beyond. In: Ma, Z. (ed.) Intelligent Databases: Technologies and Applications, pp. 238–285. Idea Group (2006)Morgan, T.: Business Rules and Information Systems - Aligning IT with Business Goals. Addison-Wesley (2002)Muñoz-Escoí, F.D., Ruiz-Fuertes, M.I., Decker, H., Armendáriz-Íñigo, J.E., de Mendívil, J.R.G.: Extending Middleware Protocols for Database Replication with Integrity Support. In: Meersman, R., Tari, Z. (eds.) OTM 2008, Part I. LNCS, vol. 5331, pp. 607–624. Springer, Heidelberg (2008)Nicolas, J.-M.: Logic for improving integrity checking in relational data bases. Acta Informatica 18, 227–253 (1982)Novakovic, I., Deletic, V.: Structuring of Business Rules in Information System Design and Architecture. Facta Universitatis Nis, Ser. Elec. Energ. 22(3), 305–312 (2009)Pipino, L., Lee, Y., Yang, R.: Data Quality Assessment. CACM 45(4), 211–218 (2002)Stonebraker, M.: Errors in Database Systems, Eventual Consistency, and the CAP Theorem (2010), http://cacm.acm.org/blog/blog-cacm/83396-errors-in-database-systems-eventual-consistency-and-the-cap-theoremStonebraker, M.: In search of database consistency. CACM 53(10), 8–9 (2010)Stonebraker, M.: Technical perspective - One size fits all: an idea whose time has come and gone. Commun. ACM 51(12), 76 (2008)Taveter, K.: Business Rules’ Approach to the Modelling, Design and Implementation of Agent-Oriented Information Systems. In: Proc. CAiSE workshop AOIS, Heidelberg (1999)Vidyasankar, K.: Serializability. In: Liu, L., Özu, T. (eds.) Encyclopedia of Database Systems, pp. 2626–2632. Springer (2009)Weikum, G., Vossen, G.: Transactional Information Systems. Morgan Kaufmann (2002)Vogels, W.: Eventually Consistent. ACM Queue 6(6), 14–19 (2008)Pereira Ziwich, P., Procpio Duarte, E., Pessoa Albini, L.: Distributed Integrity Checking for Systems with Replicated Data. In: Proc. ICPADS, vol. 1, pp. 363–369. IEEE CSP (2005