Information Management And Business Intelligence Bibliography

Annotated Bibliography
Student’s Name
Institutional Affiliation
Annotated Bibliography
Ernst & Young LLP, (2015). Information management and business intelligence. Service Brochure. Global Limited.
In the article, Ernst and Young state that many companies are increasingly recognizing data as an essential part of the business assets. They, however, point out that only a few firms have so far managed to exploit their information in the attempt to improve their business performance and boost their growth. They recognize that the application of artificial intelligence can be used by business to link their business strategies to data so that they can develop productive business models that would improve the competencies of the workers, improve management and align the organizational structure to meet the company goals. Thus, according to them, the applicability of data management and artificial intelligence in a business can be divided into seven domains; strategic alignment, data agility, data quality, tools, culture and organization, data completeness and data accessibility (Ernst & Young LLP, 2015). For example, in culture and organization, Ernst and Young state that fact-based decision making, aligning of data to possible outcomes and business collaboration are the key aspects that must be considered.
It is a useful source. The information contained is reliable and can be applied in the analysis of business and the application of artificial intelligence in data management. For example, the writers have comprehensively described the importance of artificial intelligence in information management. Some of the reasons given are that artificial intelligence combines good cross-industry competence and insights and allows for a thoughtful leadership system. However, as a limitation, the article has failed to give examples of successful application of artificial intelligence in information management. Additionally, most points are not comprehensively explained. The authors were merely giving points which make other vague. Finally, it has failed to mention the types of artificial intelligence that can be applied by firms.
As a research tool, the article has introduced me to the link between information management and artificial intelligence. It has increased my understanding of how business for data management can apply artificial intelligence. It framed my argument in a more linear perspective in that I can comprehensively argue that artificial intelligence is an excellent tool for improving company performance.
The University of Gujarat, (2015). Planning and business intelligence. IT Services.
The article is a research draft that was conducted by the University of Gujarat to determine whether businesses, especially colleges and university can apply business intelligence strategies that involve collecting and exploiting different types of information can be implemented to improve their competitive advantages. According to the article, the adoption of a good business intelligence system can improve staff management and performance by giving them useful guidelines and insights that they can apply to better the current and future state of the company. In this approach, it is essential for a business to have control of both internal and external data that explains their business structure. The researchers argue that business intelligence is a set of processes, technologies, and methodologies that can be applied to transform any raw form data into useful information that can be used by the firm to formulate policies, make business decisions and redraw their operational foundation (University of Gujarat, 2015)
In this consideration, the article proves to be very useful and reliable source. Its objectives are not biased since it had effectively used examples and evidence to support most of the arguments. Since its goal was to the applicability of business intelligence (BI) in improving the competitive advantage of a company, it has described the roles of BI in this regard. For example, in some of the university or organization, BI can be used in benchmarking, data visualization, predictive analysis, and modeling to better the performance of the firm. However, it has failed to define competitive advantage, gives examples and explain the possible limitations of applying BI to improve it.
Similarly, the article has expanded my understanding of BI, especially in improving competitive edge. It has also introduced me to the concept of competitive advantage which forms a significant factor in the success of any organization. It has diversified my understanding of artificial intelligence and business management by introducing me to the internal and external factors affecting business and data management. I can use the article develops a sound business intelligence plan.
Marchand-Maillet, S., & Hofreiter, B. (2014). Big Data Management and Analysis for Business Informatics-A Survey. Enterprise Modelling and Information Systems Architectures-An International Journal: Vol. 9, Nr. 1.
The article is a survey that was conducted to determine the applicability of business informatics in administration. In their approach, Marchand-Maillet and Hofreiter state that modern communication networks have increased the formation of vast volumes of data that are applied by business owners to control business activities. They have reviewed different technologies that have been used to empower business activities and to leverage the contents of big data. Business informatics is mostly applied in computing and information technology within the business to provide better management of data. They give a classification domain that can be used to enable and empower technologies within the business informatics.
Notably, it is a good and reliable article since it has adequately described the role of business informatics as an aspect of artificial intelligence in data management. However, it seems biased since most of its conclusions are derived majorly from the views of the writer who seem very rigid, especially modeling of trust, social labor and social knowledge which are part of the classification domain. The article is supported by good and reliable sources, and it is comprehensive in its description. However, it has failed to discuss the limitation of business informatics primarily on how it relates to the other internal factors of the business.
It has nevertheless expanded my understanding of the big data management and business informatics. The classification domain given introduced me to data management fundamentals like trust, privacy, communities, human computations and social knowledge which are also important considerations when choosing the method of artificial intelligence. I can, therefore, use to develop a user-friendly algorithm when designing the artificial intelligence.
The DATAForge Team, (2017). How Master Data Management (MDM) Supports Enterprise Business Intelligence (BI).
In this article, The DATAForge Team describes business intelligence systems, as a strategic tool that allows businesses to make good choices based on factual data. The systems use accurate inputs to allow the decision-makers to give the required outputs. The master data management is described as a holistic solution that gives direct support to the business intelligence by providing it with reliable data. However, there are different methods that MDM can use to support artificial business intelligence. First, master data management can be used to ensure consistency across with the dimensional data in a process called data cleansing. Secondly, master data management can be used to simplify the data integration business artificial intelligence system. Master data management provides a solution to the quality problem that affects data warehouses. Finally, master data management strengthens the analysis of business artificial intelligence.
Though useful, the article is not entirely reliable. It is, however, objective since most of the points given help in developing its main topic. Some of its advantages are that it has introduced the concept of master data management, which seems to be a critical foundation when designing a good artificial intelligence system in business, it is precise and has a valid argument. However, as a limitation, it has no sources provided and less information is given in the possible methods that master data management supports artificial intelligence in the business. Its relevance to the topic stems from the fact that it brings in the master data management, which is used to stabilize business data storage through BI.
It proves very useful since it has highlighted the three principal roles of master data management in boosting BI. It has diversified my understanding of artificial intelligence, and I begin to see the need of incorporating other disciplines to improve its efficiency especially in data management. I can, therefore, use it to conduct further research on master data management and how it develops data management and business intelligence navigation.
Wixom, B., Ariyachandra, T., Douglas, D. E., Goul, M., Gupta, B., Iyer, L. S., ... & Turetken, O. (2014). The current state of business intelligence in academia: The arrival of big data. CAIS, 34, 1.
The journal is an analytical review of the current use of business intelligence in academic centers like universities and colleges. In the recent past, there is an increase in the demand for artificial intelligence expertise in various fields. Business intelligence, data management, and business analytics have experienced a lot of emerging trends that have necessitated that academic sector to reformulate their syllabus to allow the learners acquire the needed knowledge. The trends are categorized based on the level of technology, predictive analytics, and visualizations applied by data managers. Big Data is very common among and has itself a number of implications. It necessitates the need to teach business analytics and intelligence to improve the innovative skills of the affected students (Wixom et al., 2014).
It is a useful and reliable source. It has an objective that focuses on a single problem statement. It brings in the contribution of the education system in improving the understanding and field application of different types of artificial intelligence by the scholars. At the moment, various schools especially ...