scholarly journals Business Intelligence Systems Accounting Integration in Romania. a Comparative Analysis

2010 ◽  
Author(s):  
Daniela Postolache (Males)
Keyword(s):  
Decision Support ◽  
Comparative Analysis ◽  
Business Intelligence ◽  
Information Integration ◽  
Accounting Information ◽  
Financial Indicators ◽  
Economic Instruments ◽  
Mobile Terminals ◽  
Business Intelligence Systems ◽  
The World

Business Intelligence (BI) systems have penetrated the Romanian market, providing a real decision support by integrating and synthesizing a large variety of information available in real time, anywhere in the world, including through mobile terminals. This study examines the BI solutions promoted in Romania through Internet sites written in Romanian, in terms of how the accounting information integration is done. Our paper highlights the most used economic and financial indicators and most often selected tools by BI systems developers to assist decisions. The writing bring forward the lack of transparency of the analyzed sites towards of configuration details of economic instruments, which we consider likely to delay the managers from Romania in order to become familiar with BI solutions, and it represent a weakness of this products promotion.

scholarly journals Üzleti intelligencia megoldások alkalmazásának sikertényezői - A hazai szolgáltató szektor nagyvállalatainak körében végzett mélyinterjús kutatás

2019 ◽  
Vol 19 (2) ◽  
pp. 23
Author(s):  
Gergely Görcsi ◽  
Gergő Barta ◽  
Zsuzsanna Széles
Keyword(s):  
Decision Support ◽  
Continuous Improvement ◽  
Business Intelligence ◽  
Support Functions ◽  
Term Operation ◽  
Success Criteria ◽  
The World ◽  
Depth Interviews ◽  
Insight Into

A vállalatok működése szempontjából a döntéstámogató funkció folyamatos fejlesztése, monitorozása kiemelt jelentőségű, hiszen az vezetést támogató eszközként segíti a menedzsmentfeladatok ellátását. Az üzleti intelligencia (business intelligence, BI) olyan infokommunikációs megoldás, mely a vállalati rendszerekből különböző adatforrásokat felhasználva képes az adatok összekapcsolására és elemzésére. A napi üzletmenet gördülékeny biztosítása céljából alkalmazott tranzakciós rendszerektől eltérően a BI-eszközök beszámolás orientáltak, a fókusz a döntéstámogatásra helyeződik. A kutatás a fogalmak tisztázását követően képet ad a legfrissebb üzleti intelligencia trendekről. A tanulmány szakmai mélyinterjúk elemzésén keresztül betekintést nyújt az üzleti intelligencia megoldások világába. A kutatás eredményeként az olvasó képet kaphat a BI bevezetésétől várt eredményekről, az implementáció és a hosszú távú működtetés sikerkritériumait illetően. --- Gergely GORCSI - Gergo BARTA - Zsuzsanna SZELES Success criteria for the application of business intelligence solutions In the running of any given company, continuous improvement and monitoring of decision support functions is crucial for such activities to serve as tools to support management tasks. Business Intelligence (BI) is an infocommunication tool that connects and analyses data from corporate systems using varied data sources. Unlike transactional systems that are used to ensure the sound operation of day-to-day business, BI tools are report-oriented, and focus on decision support. Reviewing related concepts, this research gives an overview of the latest business intelligence trends. Our study sets out to provide an insight into the world of business intelligence solutions by analysing professional, in-depth interviews. Through our research, one will become familiar with the results expected from the introduction of BI, in relation to the success criteria of its implementation and long-term operation.

Tailorable Technologies for Improving Business Intelligence Systems

2021 ◽  
pp. 560-575
Author(s):  
Shah J. Miah
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Conceptual Framework ◽  
Business Intelligence ◽  
Cost Effective ◽  
Business Owners ◽  
Business Intelligence Systems ◽  
Effective Operation

The Australian farm-based businesses can be benefited from specially designed applications for cost-effective operation while maximizing profits to survive in economic and environmental crises. For decision support, existing business intelligence systems (BIS) approaches scarcely deal with specific user's provisions to adjust changing situations in decision making, without extra technical exertions. In this chapter, the authors describe a conceptual framework of tailorable BIS solution that is based on case study findings in that the highlighted requirements are relevant to address changing situations through enhancing end user's engagement. The activities of end user's engagement supported through the use of tailorable features that reinforce a shift from the traditional BIS process to a new provision where business owners can actively involve in adjusting their features to their decision support.

Closing the Gap between Data Mining and Business Users of Business Intelligence Systems

2012 ◽  
Vol 3 (4) ◽  
pp. 14-53 ◽  
Author(s):  
Ana Azevedo ◽  
Manuel Filipe Santos
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Decision Support ◽  
Information Systems ◽  
Decision Support Systems ◽  
Business Intelligence ◽  
Easy Access ◽  
Complete Knowledge ◽  
Business Intelligence Systems ◽  
Closing The Gap

Since Lunh first used the term Business Intelligence (BI) in 1958, major transformations happened in the field of information systems and technologies, especially in the area of decision support systems. BI systems are widely used in organizations and their importance is recognized. These systems present themselves as essential parts of a complete knowledge of business and an irreplaceable tool in the support to decision making. The dissemination of data mining (DM) tools is increasing in the BI field, as well as the acknowledgment of the relevance of its usage in enterprise BI systems. BI tools are friendly, iterative, and interactive, allowing business users an easy access. The user can manipulate directly data, having the ability to extract all the value contained into that business data. Problems noted in the use of DM in the field of BI is related to the fact that DM models are complex in order to be directly manipulated by business users, not including BI tools. The nonexistence of BI tools allowing business users the direct manipulation of DM models was identified as the problem. More of these issues, possible solutions and conclusions are presented in this article.

Tailorable Technologies for Improving Business Intelligence Systems

2019 ◽  
pp. 238-253
Author(s):  
Shah J. Miah
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Conceptual Framework ◽  
Business Intelligence ◽  
Cost Effective ◽  
Business Owners ◽  
Business Intelligence Systems ◽  
Effective Operation

The Australian farm-based businesses can be benefited from specially designed applications for cost-effective operation while maximizing profits to survive in economic and environmental crises. For decision support, existing business intelligence systems (BIS) approaches scarcely deal with specific user's provisions to adjust changing situations in decision making, without extra technical exertions. In this chapter, the authors describe a conceptual framework of tailorable BIS solution that is based on case study findings in that the highlighted requirements are relevant to address changing situations through enhancing end user's engagement. The activities of end user's engagement supported through the use of tailorable features that reinforce a shift from the traditional BIS process to a new provision where business owners can actively involve in adjusting their features to their decision support.

Collaborating Decision Support and Business Intelligence to Enable Government Digital Connectivity

2021 ◽  
pp. 95-112
Author(s):  
Leu Fang Yie ◽  
Heru Susanto ◽  
Desi Setiana
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Business Intelligence ◽  
Support Systems ◽  
Positive Impact ◽  
Innovation Management ◽  
Digital Transformation ◽  
Management Approach ◽  
Critical Factors ◽  
The World

Many governments around the world are actively engaging in digital transformation, aiming to turn themselves into digital governments. Here, innovation management is one of the most critical factors for such transformation. One approach is to implement business intelligent (BI) and decision support systems (DSS). Collaboration of these two technologies is essential to bring out the best within the organizations, by way of allowing the management to make timely, effective, and correct decisions, including better processing in terms of knowledge and data that the organizations hold. Evidence suggests that implementation and collaboration of DSS and BI results in a positive impact on businesses, organizations, and governments, as well as on other related aspects of the workforce. This chapter proposes and discusses a novel implementation of innovation management approach showcasing the use of DSS and BI in achieving more open digital and connected governments.

Business Plus Intelligence Plus Technology Equals Business Intelligence

2012 ◽  
pp. 13-28
Author(s):  
Ira Yermish ◽  
Virginia Miori ◽  
John Yi ◽  
Rashmi Malhotra ◽  
Ronald Klimberg
Keyword(s):  
Information Technology ◽  
Twentieth Century ◽  
Decision Support ◽  
World Wide Web ◽  
Business Intelligence ◽  
World Wide ◽  
Mass Storage ◽  
Business Operations ◽  
The World ◽  
Technological Developments

In this article the authors will show how the parallel developments of information technology at the operational business level and decision support concepts progressed through the decades of the twentieth century with only minimal success at strategic application. They will posit that the twin technological developments of the world-wide-web and very inexpensive mass storage provided the environment to facilitate the convergence of business operations and decision support into the strategic application of business intelligence.

Tailorable Technologies for Improving Business Intelligence Systems

2021 ◽  
pp. 814-829
Author(s):  
Shah J. Miah
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Conceptual Framework ◽  
Business Intelligence ◽  
Cost Effective ◽  
Business Owners ◽  
Business Intelligence Systems ◽  
Effective Operation

The Australian farm-based businesses can be benefited from specially designed applications for cost-effective operation while maximizing profits to survive in economic and environmental crises. For decision support, existing business intelligence systems (BIS) approaches scarcely deal with specific user's provisions to adjust changing situations in decision making, without extra technical exertions. In this chapter, the authors describe a conceptual framework of tailorable BIS solution that is based on case study findings in that the highlighted requirements are relevant to address changing situations through enhancing end user's engagement. The activities of end user's engagement supported through the use of tailorable features that reinforce a shift from the traditional BIS process to a new provision where business owners can actively involve in adjusting their features to their decision support.

Business Plus Intelligence Plus Technology Equals Business Intelligence

2010 ◽  
Vol 1 (1) ◽  
pp. 48-63 ◽  
Author(s):  
Ira Yermish ◽  
Virginia Miori ◽  
John Yi ◽  
Rashmi Malhotra ◽  
Ronald Klimberg
Keyword(s):  
Information Technology ◽  
Twentieth Century ◽  
Decision Support ◽  
World Wide Web ◽  
Business Intelligence ◽  
World Wide ◽  
Mass Storage ◽  
Business Operations ◽  
The World ◽  
Technological Developments

In this article the authors will show how the parallel developments of information technology at the operational business level and decision support concepts progressed through the decades of the twentieth century with only minimal success at strategic application. They will posit that the twin technological developments of the world-wide-web and very inexpensive mass storage provided the environment to facilitate the convergence of business operations and decision support into the strategic application of business intelligence.

Commercial and Open Source Business Intelligence Platforms for Big Data Warehousing

2019 ◽  
pp. 158-181 ◽  
Author(s):  
Jorge Bernardino ◽  
Joaquim Lapa ◽  
Ana Almeida
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Decision Support ◽  
Comparative Analysis ◽  
Open Source ◽  
Data Warehouse ◽  
Business Intelligence ◽  
Selection Process ◽  
Decision Making Processes ◽  
Big Data Warehouse

A big data warehouse enables the analysis of large amounts of information that typically comes from the organization's transactional systems (OLTP). However, today's data warehouse systems do not have the capacity to handle the massive amount of data that is currently produced. Business intelligence (BI) is a collection of decision support technologies that enable executives, managers, and analysts to make better and faster decisions. Organizations must make good use of business intelligence platforms to quickly acquire desirable information from the huge volume of data to reduce the time and increase the efficiency of decision-making processes. In this chapter, the authors present a comparative analysis of commercial and open source BI tools capabilities, in order to aid organizations in the selection process of the most suitable BI platform. They also evaluated and compared six major open source BI platforms: Actuate, Jaspersoft, Jedox/Palo, Pentaho, SpagoBI, and Vanilla; and six major commercial BI platforms: IBM Cognos, Microsoft BI, MicroStrategy, Oracle BI, SAP BI, and SAS BI & Analytics.

Rationalising Business Intelligence Systems and Explicit Knowledge Objects: Improving Evidence-Based Management in Government Programs

2014 ◽  
Vol 13 (02) ◽  
pp. 1450018 ◽  
Author(s):  
Carlton E. Sapp ◽  
Thomas Mazzuchi ◽  
Shahram Sarkani
Keyword(s):  
Decision Making ◽  
Business Intelligence ◽  
Information Integration ◽  
Explicit Knowledge ◽  
Evidence Based ◽  
Government Programs ◽  
Business Intelligence Systems ◽  
Efficiency And Effectiveness ◽  
Knowledge Objects ◽  
Evidence Based Decision Making

Public sector programs often fail to leverage their business intelligence systems and explicit knowledge objects to drive efficiency and effectiveness. Given the current federal fiscal environment and the need for effective government — a catalyst to the requirement to use "evidence and rigorous evaluation in budget, management, and policy decisions" (OMB Memorandum M-12-14) — federal programs look to business intelligence as an evidence-based decision-making practice leading to a more lean government, improving efficiency and effectiveness. However, cost overruns, technical obstacles, and next-generation information challenges stemming from pervasive computing can reduce any perceived value of utilising explicit knowledge systems to support evidence in decision making. Through the evaluation of five diverse projects tasked to address the use of evidence in decision-making practices, this research shows that achieving contextualisation of information requirements, stakeholder alignment, and the complexity/feasibility of information integration are key factors that should be analysed to improve the evidence-based decision-making practice in government programs, and may be accomplished through a systematic approach, such as the rationalisation of business intelligence systems. Thus, a rationalisation framework is provided to facilitate the management of business intelligence systems geared towards a more efficient and effective use of explicit knowledge.

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