Big data challenge for monitoring quality in higher education institutions using business intelligence dashboards

As big data becomes an apparent challenge to handle when building a business intelligence(BI)system,there is a motivation to handle this challenging issue in higher education institutions(HEIs).Monitoring quality in HEIs encompasses handling huge amounts of data coming from different sources.This paper reviews big data and analyses the cases from the literature regarding quality assurance(QA)in HEIs.It also outlines a framework that can address the big data challenge in HEIs to handle QA monitoring using BI dashboards and a prototype dashboard is presented in this paper.The dashboard was developed using a utilisation tool to monitor QA in HEIs to provide visual representations of big data.The prototype dashboard enables stakeholders to monitor compliance with QA standards while addressing the big data challenge associated with the substantial volume of data managed by HEIs’QA systems.This paper also outlines how the developed system integrates big data from social media into the monitoring dashboard.

Building a Business and Strategic Intelligence Policy as a Strategy for Promoting Congolese Business Progress and Healthy Economic Development in Eastern DRC

The aim of this study was to verify the existence of business and strategic intelligence policies at the level of Congolese companies and at the state level, likely to foster progress and healthy development in the east of the DRC. The study was based on a mixed perspective consisting of objective analysis of quantitative data and interpretative analysis of qualitative data. The results showed that business and strategic intelligence policies have not been established at either company or state level, as this is an area of activity that is not known to the players in companies and public departments, and there are no units or offices in their organizational structures responsible for managing strategic information for competitiveness on the international market. In addition, there is a real need to establish strategic information management units within companies, upstream, and to set up a national strategic information management department or agency to help local companies compete in the marketplace, downstream. This reflects the importance and timeliness of building business and strategic intelligence policies to ensure economic progress and development in the eastern DRC. Business and strategic intelligence provides companies with an appropriate tool for researching, collecting, processing and disseminating information useful for decision-making among stakeholders, in order to cope with a crisis or competitive situation. The study suggests a number of key recommendations based on its findings. To the government, it is recommended to establish the national policy of business and strategic intelligence by setting up a national agency of strategic intelligence in favor of local companies;and to companies to establish business intelligence units in their organizational structures in favor of stakeholders to foster advantageous decision-making in the competitive market and achieve progress. Finally, the study suggests that studies be carried out to fully understand the opportunities and impact of business and strategic intelligence in African countries, particularly in the DRC.

Big Data 4.0: The Era of Big Intelligence

Big data has had significant impacts on our lives,economies,academia and industries over the past decade.The current equations are:What is the future of big data?What era do we live in?This article addresses these questions by looking at meta as an operation and argues that we are living in the era of big intelligence through analyzing from meta(big data)to big intelligence.More specifically,this article will analyze big data from an evolutionary perspective.The article overviews data,information,knowledge,and intelligence(DIKI)and reveals their relationships.After analyzing meta as an operation,this article explores Meta(DIKE)and its relationship.It reveals 5 Bigs consisting of big data,big information,big knowledge,big intelligence and big analytics.Applying meta on 5 Bigs,this article infers that 4 Big Data 4.0=meta(big data)=big intelligence.This article analyzes how intelligent big analytics support big intelligence.The proposed approach in this research might facilitate the research and development of big data,big data analytics,business intelligence,artificial intelligence,and data science.

Business Intelligence as a Service——SaaS BI Introduction and Recommendations

Characterized as automated access,analysis,management,improvement,identification,and efficiency,SaaS BI has played a significant role recently. This essay presents information about SaaS BI,such as,the generic reason for prevalent,advantages and limitations of SaaS BI,current market overview,tendency of development of SaaS BI,and applications in business. This paper uses the literature study and descriptive study methods in order to analysis the influence and functions of SaaS BI to the businesses and coping strategies.

基于大数据BI技术的智慧工地数据可视化平台的设计与研究--以某大型建筑工程集团为例

大数据BI(Business Intelligence)技术在数据挖掘、数据分析、数据可视化等方面的功能实现较成熟,已广泛应用在制造业、零售业等行业。将大数据BI技术融入智慧工地,建立数据可视化平台,可以解决智慧工地存在的局部“数据孤岛”等问题,让智慧工地的海量数据得到最大价值体现。文章以某大型市政特级资质建筑工程集团为例,采用基于Hadoop+Spark的技术架构,以在建的大型地铁市政工程项目为实践,主要论述数据可视化平台架构选型、建立数据仓库、数据ETL、数据可视、Spark引擎框架与MapReduce在数据处理性能方面的对比等。构建基于大数据BI技术的智慧工地可视化数据平台,能有效推进智慧工地的开展,提升对工程项目在质量安全、绿色施工、成本管控等方面的管理。

基于Power BI的DRGs数据分析方法

目的:探讨利用Power BI工具对DRGs数据进行有效分析,揭示潜在的数据特征和规律。方法:运用Power BI工具对2017年―2021年DRGs数据进行数据连接、数据清洗和处理等操作,提取和计算相关DRGs评价指标,最后通过可视化展示的方式对DRGs数据进行分析和呈现,从不同维度和角度深入研究DRGs数据特征和规律。结果:通过对2017年―2021年DRGs数据处理和可视化展示,能直观了解出院患者疾病构成、医疗资源利用、临床质量评估和医疗成本效益等总体情况,为提高医疗服务质量和资源利用效率等提供可行的解决方案。结论:基于Power BI的DRGs数据分析方法能够有效地帮助医院进行医疗费用控制和资源配置,并提高医疗服务的质量和效率。此方法为优化DRGs数据管理和医疗资源配置提供了重要的参考和借鉴价值。

基于FineBI的集中采购药品数据分析与可视化展示

目的利用可视化工具FineBI对集中采购药品进行数据分析和处理,进行可视化展示,形成的监测报表可作为药学部门决策参考。方法先用Excel处理从医院系统中导出来的集采药品采购量、销售量等原始数据,然后根据药品管理需求,用Fi neBI对数据处理,形成可视化图表。结果生成集采药品采购进度查询、销售详情、药理作用分布、同通用名药品使用情况、可替代药品监测等可视化图形,可视化报表能在电脑端和移动端分享联动。结论应用FineBI软件对集采药品数据处理,能够形成精细化、数字化、可视化程度高的报表,有助于药师开展集采药品数据分析工作。

基于BI的大型公立医院绩效管理系统设计与应用

为了提升医院绩效考核管理效率,基于商业智能(BI)技术,构建区域大型公立医院绩效管理系统。系统包括商业智能分析子系统、Web应用过程子系统和后台数据库三个部分。采用成熟的Windows操作系统、Java EE开发技术,后台数据库采用Oracle OBIEE平台,确保系统运行的稳定性;系统软件基于B/S构建了表示层、业务逻辑层、数据层三层架构,确保了系统简单易操作,同时受众面广等特点;系统数据库采用事实星座模式进行构建,确保系统具备高速运行速度和升级扩展影响性。通过商业智能技术与Web应用过程子系统的完美衔接,构建起医院绩效分析平台。该平台可实现绩效指标查询、提取、打印等6大功能。通过黑盒测试法和Load Runner测试软件对系统功能和性能进行了测试,结果表明,系统各项功能均符合预期,系统响应时间均控制在3 s以内。

基于改进Bi-LSTM-CRF的农业问答系统研究

针对农业领域问答系统面临的实体识别困难的问题,提出一种基于改进Bi-LSTM-CRF的实体识别方法。首先通过BERT预训练模型的预处理,生成基于上下文信息的词向量,然后将训练出的词向量输入Bi-LSTM-CRF做进一步的训练处理,最后,利用Python的Django框架设计农业领域的实体识别、实体查询、农知问答等子系统。经过试验对比,所提出的改进的Bi-LSTM-CRF在农业信息领域具有更好的实体识别能力,在农业信息语料库上的精确率、召回率和F1值分别为93.23%、91.08%和92.16%。实现农业领域实体识别和农业信息问答的知识图谱网站演示,对农业信息化的发展具有重要意义。

BI:为信息化冲刺——访Business Objects公司中国区董事、总经理杨君霈先生

如果你还没有实施电子商务智能战略,那么现在应该开始准备起来了。你的竞争对手如果也还没有实施电子商务智能,他们必然迟早会这么做的,这只是个时间问题。如果你以更好的质量和更快的速度建立电子商务智能系统的话,企业的运营将更有效,你对业务的理解也将会更加深入,另外你的客户将享受更好的服务。最终,你将获得关键的竞争优势!——摘自Business Objects公司总裁 Bernard Liautaud先生的《商务智能》

基于Power BI软件对集采药品的智能监测与管理

目的提高国家组织药品集中采购、省际联盟带量采购药品(简称集采药品)工作监控管理的智能化水平。方法基于Power BI软件开发可视化智能监控工具,获取并整理数据,运用M函数与度量值对数据建模分析,添加视觉对象生成交互式可视化报表。结果基于Power BI软件自主设计集采药品智能监控系统实现了以集采药品为业务场景的多维分析,可快速获取集采药品的合同量完成情况、中选与非中选药品采购量占比、采购金额占比等重要指标。结论Power BI软件可为医院集采药品的管理提供强大的技术支持,并可实现数据使用规范化、统计分析智能化、数据呈现可视化。

Business Intelligence Expert System on SOX Compliance over the Purchase Orders Creation Process

The objective of this work is to define a decision support system over SOX (Sarbanes-Oxley Act) compatibility and quality of the Purchase Orders Creation Process based on Artificial Intelligence and Theory of Argumentation knowledge and techniques. This proposed model directly contributes to both scientific research artificial intelligent area and business practices. From business perspective it empowers the use of artificial intelligent models and techniques to drive decision making processes over financial statements. From scientific and research area the impact is based on the combination of 1) an Information Seeking Dialog Protocol in which a requestor agent inquires the business case, 2) a Facts Valuation based Protocol in which the previously gathered facts are analyzed, 3) the already incorporated initial knowledge of a human expert via initial beliefs, 4) the Intra-Agent Decision Making Protocol based on deductive argumentation and 5) the semi automated Dynamic Knowledge Learning Protocol. Last but not least the suggested way of integration of this proposed model in a higher level multiagent intelligent system in which a Joint Deliberative Dialog Protocol and an Inter-Agent Decision Deductive Argumentation Making Protocol are described.

On Computing the Suitability of Non-Human Resources for Business Process Analysis

Business process improvement is a systematic approach used by several organizations to continuously improve their quality of service.Integral to that is analyzing the current performance of each task of the process and assigning the most appropriate resources to each task.In continuation of our previous work,we categorize resources into human and non-human resources.For instance,in the healthcare domain,human resources include doctors,nurses,and other associated staff responsible for the execution of healthcare activities;whereas the non-human resources include surgical and other equipment needed for execution.In this study,we contend that the two types of resources(human and non-human)have a different impact on the process performance,so their suitability should be measured differently.However,no work has been done to evaluate the suitability of non-human resources for the tasks of a process.Consequently,it becomes difficult to identify and subsequently overcome the inefficiencies caused by the non-human resources to the task.To address this problem,we present a three-step method to compute a suitability score of non-human resources for the task.As an evaluation of the proposed method,a healthcare case study is used to illustrate the applicability of the proposed method.Furthermore,we performed a controlled experiment to evaluate the usability of the proposed method.The encouraging response shows the usefulness of the proposed method.

Web Application Commercial Design for Financial Entities Based on Business Intelligence

Multiple customer data management has become a focus of attention in big organizations.Although much information is available,it does not translate into significant profitable value-added services.We present a design of a commercial web application based on business intelligence that generates information on social and financial behavior of clients in an organization;with the purpose of obtain additional information that allows to get more profits.This app will provide a broader perspective for making strategic decisions to increase profits and reduce internal investment costs.A case in point is the financial sector,a group of financial entities were used to make measurements and test them.A design to build a web application aimed at achieving a large and ambitious goal by means of defined tools reflecting clients’business needs is proposed.In this research,different techniques and technologies are explored,such as diagrams,frameworks,design,architecture,model entity-relationship,tables,equations,mental maps and development tools.Through the Personal Software Process methodology and with the help of information extraction,consolidation,and visualization,the implementation can be carried out.This article provides the importance of implementing business intelligence in an organization and expands on the steps needed for the implementation of this valuable technology.

Competency Driven Resource Evaluation Method for Business Process Intelligence

Enterprises are continuously aiming at improving the execution of processes to achieve a competitive edge.One of the established ways of improving process performance is to assign the most appropriate resources to each task of the process.However,evaluations of business process improvement approaches have established that a method that can guide decision-makers to identify the most appropriate resources for a task of process improvement in a structured way,is missing.It is because the relationship between resources and tasks is less understood and advancement in business process intelligence is also ignored.To address this problem an integrated resource classification framework is presenting that identifies competence,suitability,and preference as the relationship of task with resources.But,only the competence relationship of human resources with a task is presented in this research as a resource competence model.Furthermore,the competency calculation method is presented as a user guider layer for business process intelligencebased resource competence evaluation.The computed capabilities serve as a basic input for choosing the most appropriate resources for each task of the process.Applicability of method is illustrated through a heathcare case study.

Replacing the Annual Budget with Business Intelligence Driver-Based Forecasts

The fixed annual budget process can be a cumbersome and static process, often failing to deliver intended benefits. Typically detached from business operations and strategic planning goals, the annual budget suffers from inherent weaknesses caused by a lack of business intelligence regarding its underlying assumptions. This weakness is well documented in existing literature and there is ample evidence of improved alternatives to static corporate financial planning. One such alternative utilizes business intelligence as an essential component in the annual budget process, along with rolling forecasts as a critical tool. Utilizing business intelligence supported, driver-based rolling forecasting can align an organization’s budget process with strategic objectives and can further the operational and financial strength of an organization, as well as maximize shareholder value. In order to fully explore this topic, this article will present a review of the conventional annual budget process and the manner in which an approach that bases financial forecasts on business intelligence drivers can align operations with strategic objectives and add value to an organization. An assessment of intelligence-supported, driver-based rolling forecasting will also be presented, demonstrating an im- proved approach to the traditional annual budgeting process.

An OWL-Based Mobile GeoBI Context Ontology Enabling Location-Based and Context-Based Reasoning and Supporting Contextual Business Analysis

Mobile professionals need to be assisted with suitable mobile GeoBI (Geospatial Business Intelligence) systems, which are able to capture, organize and structure the user’s reality into a relevant context model and reason on it. GeoBI context modelling and reasoning are still research issues since there is not yet either a model or a relevant taxonomy regarding GeoBI contextual information. To fill this gap, this paper proposes an extended and detailed OWL-based mobile GeoBI context ontology to provide context-aware applications and users with relevant contextual information and context-based reasoning capabilities. Context quality issues are handled an implementation architecture which is provided.