FIGURE 1 - available via license: CC BY
Content may be subject to copyright.
Source publication
Background: Business intelligence tools play an important role for businesses across all industries for their data and information management solutions. By harnessing the capabilities of business intelligence, companies are able to predict and better meet customer needs. This study investigates factors that inhibit managers’ use of business intelli...
Context in source publication
Context 1
... ]ithin the model for business intelligence maturity, there are four levels in which an organisation can be classified in terms of levels of information of increasing value to business strategy. Figure 1 depicts the questions which, according to Gartner (2016), managers should be able to answer from the use of business intelligence tools: ...
Similar publications
South Africa needs a coordinated strategy to prepare school learners for higher education in the disciplines of Science, Technology, Engineering and Mathematics in particular. Mathematics as a core discipline requires problem-solving knowledge and skills essential to 21 st-century demands. However, many secondary school learners do not have the req...
Citations
... Tešendić and Krstićev (2019) Business intelligence (BI) refers to methodologies, analytical tools, and applications used for data analysis of business information. Mansell and Ruhode (2019) Business intelligence tools play an important role for businesses across all industries for their data and information management solutions. By harnessing the capabilities of business intelligence, companies are able to predict and better meet customer needs. ...
In this chapter, the business intelligence and social media analytics (SMA) are brought into focus to address the strategies, methods, and technologies for managing the data analysis processes. The overall goal is to identify differences in categories, tools, and techniques concerning the development of various analytics processes as well as their application and obtained results in cultural heritage businesses. The focus is on business intelligence and social media analytics to partnering business activities towards the achievement of better results from different perspectives, such as efficiency, interactivity with customers, improvement of internal processes, and a wiser decision-making process based on information. To clarify the theoretical and practical implications on the field, several examples of results achieved by firms that have implemented business intelligence and social media analytics in their daily activities are illustrated.
Due to hundreds of millions of financial transactions that take place
daily in the financial sector, Big Data has become a buzzword and a crucial
component in financial business operations. Consequently, handling this data is
becoming a major concern for many financial services. Much as this is so, the
nature in which this data is generated makes it complex to analyse using
traditional database management systems. Little empirical research has been
done to inform financial organisations on how to analyse Big Data to improve
business agility and competitiveness. More still, there is a lack of an appropriate
model that could be used by financial organisations to carry out Big Data
analytics. This paper sought to conceptualise a model for Big Data analytics to
improve organisational competitiveness by taking the case of South African
financial institutions. Collected data was analysed quantitatively and results
indicated that technological, organisational, and environmental perspectives
along with individual factors play a significant role in Big Data analytics
improving financial institutions’ competitiveness. The identified factors were
used to conceptualise a model that could be used to extend research in this
direction. Results of the study revealed that as new trends in computing increase,
traditional analytics currently used by many organisations gradually become
obsolete hence it is recommended that the developed model be validated with a
wide range of data from various organisations to identify the new factors that
might be salient.
Climate change information plays a pivotal role in decision-making on what crop to plant, what time to water the plant/mulch the field, what type of fertilizer to apply, and at what time. As such, small-scale rural farmers need to get climate information in real-time and in their mother language since English is a barrier. Therefore, this study assessed how climate information is disseminated to rural small-scale farmers in Raymond Mhlaba municipality, the challenges faced, and evaluated the effectiveness of the modes of disseminating climate information used currently. A Participatory Action Research methodology was adopted being informed by literature review and focus group methods. The data was collected from thirty farmers, four extension officers, and four climate and weather experts who acted as key informants. To remove bias, a randomization approach was used. SPSS software was used to analyze part of the results and draw graphs and pie charts. Results showed that 90% of the farmers receive climate information from newspapers, dramas, television, and radio. Only 10% receive information via short message service on their phones even though all the farmers own a simple cellphone. Of the 90%, 70% received their climate information through radio which proved to be widely used for the dissemination of climate information among rural small-scale farmers. These results served as a basis for a technological intervention to improve accurate collection and real-time dissemination of climate information to rural small-scale farmers using mobile phones.
La inteligencia de negocios y la analítica de datos en los procesos empresariales se aplican en varios sectores organizacionales, este último representa un factor de ventaja competitiva, para este fin es necesario utilizar herramientas tecnológicas y definir los procesos que permitan generar modelos maduros de gestión, mientras que la inteligencia de negocios y la analítica de datos representan, como estrategia empresarial, es un factor importante de rendimiento y toma de decisiones. El objetivo fue establecer un marco de referencia teórica de la inteligencia de negocios y la analítica de datos en los procesos empresariales, en este artículo se revisaron artículos de revista indizadas en SCOPUS, Web of Science y Scielo a través del uso de google académico, el rango de revisión fue entre los años 2017 y 2021. Los resultados revelaron que el sector empresarial es donde se aplican con mayor frecuencia las soluciones en inteligencia de negocios y analítica de datos, además la metodología empírica es la más aplicada. Se concluyó que este estudio constituye un marco de referencia teórica para futuras investigaciones sobre la inteligencia de negocios y la analítica de datos en los procesos empresariales.
