Establishing banking data mart for evaluation of credit exposure

Main objective of thesis is the presentation of the evolution of the data mart in banking data warehouse of credit exposure. In the first part we focus on the basics of data warehouse, describe different approaches to building it and some differences between the warehouse and operational data base. We define architecture and highlight some trends of data warehousing. In the second section we focuse on the specifics of the banking data warehouse and exposure some disadvantages in the construction it. We describe and illustrate the case of implementation of credit exposure into data warehouse. We described a dimensional data model, ETL processes for loading data and producing reports to assist in decision-making and reporting. In thesis we present a tool for implementation of ETL processes IBM DataStage and tool for creating reports BusinessObject SAP BI. We conclude the work with the effects and results of the data mart construction in a banking data warehouse for credit exposure

Establishing banking data mart for evaluation of credit exposure

Main objective of thesis is the presentation of the evolution of the data mart in banking data warehouse of credit exposure. In the first part we focus on the basics of data warehouse, describe different approaches to building it and some differences between the warehouse and operational data base. We define architecture and highlight some trends of data warehousing. In the second section we focuse on the specifics of the banking data warehouse and exposure some disadvantages in the construction it. We describe and illustrate the case of implementation of credit exposure into data warehouse. We described a dimensional data model, ETL processes for loading data and producing reports to assist in decision-making and reporting. In thesis we present a tool for implementation of ETL processes IBM DataStage and tool for creating reports BusinessObject SAP BI. We conclude the work with the effects and results of the data mart construction in a banking data warehouse for credit exposure

Improving lifecycle query in integrated toolchains using linked data and MQTT-based data warehousing

The development of increasingly complex IoT systems requires large engineering environments. These environments generally consist of tools from different vendors and are not necessarily integrated well with each other. In order to automate various analyses, queries across resources from multiple tools have to be executed in parallel to the engineering activities. In this paper, we identify the necessary requirements on such a query capability and evaluate different architectures according to these requirements. We propose an improved lifecycle query architecture, which builds upon the existing Tracked Resource Set (TRS) protocol, and complements it with the MQTT messaging protocol in order to allow the data in the warehouse to be kept updated in real-time. As part of the case study focusing on the development of an IoT automated warehouse, this architecture was implemented for a toolchain integrated using RESTful microservices and linked data.Comment: 12 pages, worksho

Heterogeneous biomedical database integration using a hybrid strategy: a p53 cancer research database.

Complex problems in life science research give rise to multidisciplinary collaboration, and hence, to the need for heterogeneous database integration. The tumor suppressor p53 is mutated in close to 50% of human cancers, and a small drug-like molecule with the ability to restore native function to cancerous p53 mutants is a long-held medical goal of cancer treatment. The Cancer Research DataBase (CRDB) was designed in support of a project to find such small molecules. As a cancer informatics project, the CRDB involved small molecule data, computational docking results, functional assays, and protein structure data. As an example of the hybrid strategy for data integration, it combined the mediation and data warehousing approaches. This paper uses the CRDB to illustrate the hybrid strategy as a viable approach to heterogeneous data integration in biomedicine, and provides a design method for those considering similar systems. More efficient data sharing implies increased productivity, and, hopefully, improved chances of success in cancer research. (Code and database schemas are freely downloadable, http://www.igb.uci.edu/research/research.html.)

The WebStand Project

In this paper we present the state of advancement of the French ANR WebStand project. The objective of this project is to construct a customizable XML based warehouse platform to acquire, transform, analyze, store, query and export data from the web, in particular mailing lists, with the final intension of using this data to perform sociological studies focused on social groups of World Wide Web, with a specific emphasis on the temporal aspects of this data. We are currently using this system to analyze the standardization process of the W3C, through its social network of standard setters

DATA WAREHOUSE AND BUSINESS INTELLIGENCE STRATEGIES AND TRENDS

In recent decades following the evolution of information technology, decision support systems have played an important role by presenting the necessary information resulted from the operational systems processes. By continuing improvement of the methods as well as the contribution of technological advance the applicability of decision support systems is now generalized and has reached the status of complex systems of business intelligence. Business Intelligence is about creating intelligence about a business based on a cyclic flow which consists of capturing, analyzing, planning and implementation resulting in streamlining the organization.Decisions, DSS, Data Driven, Business Intelligence, Data Warehouse