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Banking Business Intelligence - Coursework Example

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The paper "Banking Business Intelligence" is an outstanding example of business coursework. Maintaining competitive direct contact with an increasing number of customers in various banks is a vital idea that has to be fostered by any bank. As such, growing with a large number of channels oriented applications such as e-commerce, and customer communication centers are geared towards increasing the quality of service…
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A RESEARCH REPORT ON BANKING BUSINESS INTELLIGENCE Student’s name Course &Code Professor’s name University City Date A Research Report on Banking Business Intelligence Abstract Maintaining a competitive direct contact with an increasing number of customers in various banks is a vital idea that has to be fostered by any bank. As such, growing with a large number of channels oriented applications such as e-commerce, and customer communication centers are geared towards increasing quality of service provided by various business firms. Data management is a fundamental tool that any bank has to embrace for easy retrieval upon request. Consequently, proper storage of data in any financial institution helps the managing team make informed decisions about various market demands. Essentially, accurate data management leads to successful way of integrating project applications in the authentic time. In the recent past, data management in various banks has been a big challenge. Banks have lost crucial data and fraud transactions have been made in the various banks. Currently, the situation has been curbed since Business Intelligence plays a fundamental role in analysis and financial transactions tracking. The BI tools and systems are used by various banking companies to help improve quality of service delivered to their respective clients. In this regard, BI aids in constant customer connection since the systems operate online. Various clients from different banks can access services and products at their own conform. Automatic transactions have led to service quick delivery to various banks. The BI tools help in market predictions hence fostering a competitive market environment for various banks. As a result, this research report explores various concepts of BI, its component, benefits, factors that influence BI in banking and critical success factors that might influence implementation of BI tools in banking. The paper will outline an effective procedural recommendation that will lead to later implementation and use of BI systems in banking. Contents CHAPTER 1 3 1.0 Introduction 3 1.1 Background Information to the Research Topic 4 1.2 Key Components of BI in Banking 5 CHAPTER 2 7 2.0 Benefits of BI in Banking 7 CHAPTER 3 11 3.0 Implications of the use of business intelligence in the banking sector 11 3.1 The need for a chief intelligence officer 11 3.2 Alternative Conceptualization 12 3.3 Technology Acceptance Models: Bridging the Gap Between Theory and Industry 12 3.4 Looking into the future 13 3.5 Business Intelligence in Modern Marketing 14 3.6 Outsourcing 15 4.0 Conclusion 15 5.0 Reference List 19 CHAPTER 1 1.0 Introduction Current bank's operations have various ways of responding to specific challenges that befall them. Essentially, banks are mostly affected by the problem of automation of services, increased number of clients, stiff completion from other competitive banks and acquisition of new products based on innovation and development (Bogdan & Emina, 2015). These challenges affect various modern banks in the delivery of services to their customers. Handling these challenges does not guarantee safety to bank operations since other risks affect the bank. Evidently, the banks in the process of handling market challenges have to consider curbing various risks and harmonizing their business operations with the global growth of financial regulations. In this regard, the banks management team has to be effective to ensure a competitive business environment. The decisions made by the bank have to be ideal, timely and relevant to the current market situation that helps in preventing a decrease in service delivery (Adelman et al., 2013). Experience has proved that transaction database of various banks can be erased or tampered with in various business situations. Consequently, a lasting solution needs to be taken to help solve various challenges that affect banking systems. Consideration of Business Intelligence (BI) plays a pivotal role in solving both technological problems and other risks that hinder accurate and quality service delivery. As such, this retrospect research report seeks to explain broadly the application of Business Intelligence in the banking industry. 1.1 Background Information to the Research Topic A long time ago banks had a lot of data but lacked knowledge in many aspects of their operations (Inmon, 2013). The transactional database sometimes disappeared from the bank systems causing a lot of troubles and confusions. Essentially, management of the client’s reports became a big challenge to various banks. There was no established platform that could offer directions on how to operate various aspects of financial transactions to the customers (Bogdan & Emina, 2015). As a result, various banks had to seek for IT specialists to come up with a suitable criterion of ensuring faster and quality service delivery. The IT personnel spends a lot of time analyzing and producing bank reports to various customers. This did not satisfy the needs of the bank and the clients. Consequently, the Information Communication Technologies invented various technological operations that automated financial transactions. All services that are offered under the ICT department in various banks that provides solutions top market demands are classified under Business Intelligence. Essentially, BI solved various transactional problems that were affecting various banks. Nowadays, BI encompasses elements of ICT, business strategy, and marketing (Stackowiak et al., 2014). Apparently, applying BI in banking industries helps in solving various challenges that face banks in relation to management of risks and market demands. Evidently, banks that embraced BI make considerable profits from their service delivery. New product development and innovation that helps in boosting the marketing department of banks is done correctly by the use of BI. Essentially, BI provides an appropriate platform for market research that helps various banks determine various types of services demanded at specific times (Tvrdikova, 2013). BI analyzes market services that are provided by other banks to clients and gives the marketing personnel a glimpse of what lacks in the market. As a result, the team comes up with an idea in relation to Innovation and Development department to try in a specified location. The success of this trial leads to implementation of the ideas which results in rapid growth of the bank. The bank gains maximum profit and pose stiff competition to other banks ensuring a competitive market situation (Zeng et al., 2015) 1.2 Key Components of BI in Banking Business Intelligence has two main distinct meanings. The primary and less frequent meaning of BI involves human intelligence in handling business matters. On the other hand, BI means a field of investigation that covers human cognitive aspect in relation to skillful developments that aim at improving business services (Ranjan, 2015). Essentially, for banks to maintain direct contact with a large number of customers, it has to apply BI in their service delivery. As a result, the major components of BI in banking include but not limited to the following. Firstly, there is Online Analytical Process (OLAP). This involves ways in which various business users can slice their ways into a specific data from a bank using online sophisticated tools(Bogdan & Emina, 2015). The tools used allow aid the users to access multidimensional information about a specific bank based on time and hierarchies. OLAP as a BI component provides an efficient way in which various clients can access their bank data quickly in an analyzed way. The component automatically analyzes the available data to various users. Essentially, OLAP plays a pivotal role in decision making by the managing directors of the various banks. Apparently, automatic analysis of data presents the real state of the bank to managers (Curt Hall, 2013). In this regard, the management of the bank makes an informed decision about a certain aspect of the banking system. Additionally, OLAP provides vital information to the marketing department of the bank. The marketing team uses OLAP as one of the BI components to analyze market demand. This enables them to come up with an effective marketing design. Secondly, advanced analytic is another vital component of BI (Bogdan & Emina, 2015). This component involves data forecasting analysis. It uses the current data to predict various future market changes. It is statically oriented and provides information in figures, and other data analyzing tools that lead to easy interpretation. It helps various banks to come up solutions that might curb future predicted challenges and risks. Thirdly, there is company performance management (Nadeem,&Jffri,2015). This component has various aspects that aid in its effective usage. Some of the subcomponents of company performance management are portals, dashboards and scorecards (Bogdan & Emina, 2015). This component helps to guide customers to services that are provided for a specific bank. A customer only needs to log into the banks portal or view its website to see various services that are offered by a specific bank. As such, they help to increase market demand for the components serve as an educator to the customers. Thirdly, there is data BI real time (Lee, &Park, 2015). This component helps in the provision of the real bank situation to both clients and managers. It gives general information about certain aspects of the bank that need to be attended to. It helps in the prediction of challenges and risks that might affect the bank. Lastly, there is Data Storehouse and Data Marts (Mosimann, & Connelly,2014). This component helps in the storage of data of a particular bank. The data is stored safely, and it cannot be tampered with. Upon request, the stored data generates itself automatically to provide the needed information. It is a vital tool for both clients and the whole bank staff. The component stores information for a long period. Use of this component can easily trace the bank history. Transactions of a particular client can be auto-retrieved upon request since the component works automatically. It is a fundamental BI component since it keeps track of all transactions, changes, progress and losses that are made by the bank (Jonathan, 2013). CHAPTER 2 2.0 Benefits of BI in Banking BI as a fore mentioned is a vital tool that helps in faster and quality service provision in a specified bank. As such, it has numerous benefits to various banks that adopted it since its creation. Some of the benefits of BI to various financial institutions offering banking services include but not limited to the following. Firstly, it helps various banks to make a well informed decision about a certain aspect (Davenport, 2013). For example, BI has enabled The Bank of America to become a competitive banking institution in the world. All financial transactions in this bank are done based on BI services that are done and generated automatically (Davenport, 2013). Essentially, BI has posed a competitive market advantage to various financial institutions since it aims at quick and quality service provision. It has ensured that services provided by various financial institutions are of high quality. Secondly, the main objective of BI is to improve timelessness, quality, and reliable service delivery. Consequently, various banks that effectively implemented BI in their service delivery provide the most reliable services (Goebel,& Le, 2014). For example, The Bank of Australia embraced BI in its early development. In this regard, this bank has been able to grow rapidly since customers have trust in it. Banking errors that mostly affect banks were done away with in this bank. As such, client reliability is prioritized by this bank hence increasing market demand. Essentially, banks that successfully implement BI in their financial transactions are always reliable since the system is proved to be reliable. Thirdly, BI aids in the establishment of the exact position of various banks in comparison to other competitors (Turban & McLean, 2013). BI has components that automatically analyze the progress made by a specified bank. Additionally, the component presents the progress made by other banks. This is a fundamental tool in any business organization since it helps business to make vital choices that aim at improving the quality of service provided. Quality improvement is vital since it helps in posing a competitive business environment in a specified market situation (Simon,2013). For example, the Australian Commercial Bank can come up with various ways of competing with other Australian financial services offering banking through the use of BI components. The bank makes various changes that help in posing a healthy competition to other banks. As a result, the bank affords to survive in a competitive business environment. Fourthly, BI helps the bank to make various changes that relate to customer behavior and spending patterns (Tim,2013). The banks can alter rates of banking in relation to customer reactions. Simply put BI shows customer reaction to various financial rate changes in a specified bank. Essentially, drop in customer deposits and withdrawal will be shown by the BI components that help the bank to make necessary changes. The changes to be made will be customer friendly and will retain the customers and attract new ones. This result in a competitive business environment since the decision made all focus on customer satisfactory (Cohen, 2014). Fifthly, BI aids in the establishment of market conditions, prediction of future trends and provision of economic information (Golfarelli et al., 2014). This helps various banks to develop a well-placed financial transaction that aids in service quick delivery. Market conditions help banks to make various changes that suit in a specific market environment. The changes made are specifically customer oriented. For instance, the World Bank uses BI in its business transactions. As such, every client across the globe can access its services quickly. In this regard, the bank can predict market conditions based on customer feedback. The response of customers is discovered from the analytical tools of BI. Prediction of future business trends is enabled by the bank since the BI presents an accurate business situation. Other benefits of BI in banking include, discovery of money laundering, analyzing of potential customers, determinations of product and service that aims at quality service delivery, detection of deter fraudamong bank staffs among other. This benefits help in maintaining a competitive business environment that suits market demands (Malhotra, 2013). CHAPTER 3 3.0 Implications of the use of business intelligence in the banking sector 3.1 The need for a chief intelligence officer In order to assist in building and maintaining the ability of a learning organization to leverage its knowledge and intelligence is for the CEO to place the knowledge and intelligence at the fingertips of every employee. The CEO handles shaping the vision of the organization and building both internal and external networks to sustain it. However, due to the time and responsibilities of the CEO, this task is often passed on to another individual, most of the time with the right expertise and time to carry out the duties. A specific title is required to make sure business intelligence is useful to the company. The formulation of the internal and external systems by the CEO or top level management means information will be available to employees, backed up by their experience regarding the company, its products, history, customers and internal technology and processes. Business intelligence, most of the time at least, results in information being held in bits and pieces across various sections of the company by different individuals. Having one central officer in charge of knowledge and intelligence can ensure the transfer of this information to all sectors of the business. The shared knowledge and intelligence can be a powerful resource. Change is the only constant in the banking sector. The chief officer in charge of the intelligence and knowledge must realize this and make sure that they incorporate it into the activities of the organization. This individual will be judged on the ability of the company to leverage the benefits of business intelligence to survive change even when they are not around, and their ability to assist the critical decision makers in functional areas of the company (Thierauf, 2001). This is the only true comprehensive way to understand and anticipate the changing needs of the customer and approaches of the competition. 3.2 Alternative Conceptualization Many people view the concept of business intelligence as a step by step and linear implementation of technology. A study of the benefits and critical success factors of business intelligence highlights important implications for banks. While knowledge and experience are crucial, business intelligence fails if people ignore the information and make decisions based on their knowledge and intuition. Studies have also revealed that successful business intelligence practices must have self-reinforcing aspects (Henfridsson & Bygstad, 2013). Business intelligence must be approached as an information infrastructure. Information infrastructure is a shared, evolving, open and heterogeneous system. It consists of IT capabilities and user, design and operations communities. Being shared and open means several players can access the system and in some instances make changes. Changes made by one actor can only add value to the other players. Being heterogeneous means it has various technologies that are constantly evolving and have various user, groups. It should be an evolving socio-technical system, indicating it often does not have a clear start (Hanseth & Lyytinen, 2010). 3.3 Technology Acceptance Models: Bridging the Gap Between Theory and Industry While there have been substantial studies on the results of business intelligence systems in the banking sector, these studies have had glaring inadequacies. Many of them only focus on the technical or business aspect, forgetting about one critical success factor in the implementation of business intelligence, the people. Emerging information technology cannot generate the expected outcomes without the right levels of acceptance by the potential users. There must be perceived ease of use and usefulness by the potential users and beneficiaries of the business intelligence system. These in turn determine the behavioral intentions towards the use of information technology (Kamara, 2014). This ease of use and usefulness must be understood across the board at all managerial levels. The banking sector, and the corporate sector, in general continues to bank on managerial efficiency at all levels. Generally, in the past attention focused a lot on the activities of lower level employees and how to improve their efficiency. Viewed from a strictly financial perspective, productivity and labor of lower level workers is only a fraction of the organizational productivity. The manager makes decisions and not products, so its timeliness defines the effectiveness of their action. Both the productivity and input at lower and high-level managerial decision making are important. Research shows that participatory decision making is more effective to create products that will receive widespread acceptance in the market (Thierauf, 2001). To involve everyone in the decision-making structure, business intelligence must be accepted across the board. 3.4 Looking into the future In the past, business intelligence has been mainly used as a post-mortem tool. Even in the banking sector with its unique characteristics, most of the time information gathering has been in response to problems with regards to finding out what went wrong and made sure it does not happen again. This reactionary approach normally means performance improvement cycles are not as fast enough in response to the needs of clients and the events of other financial sectors. The recession of 2008 was an eye-opener, though, and brought with it new implications in terms of the use of business intelligence. Banks have achieved reasonable success and stability in the use of business intelligence in maintaining the business-as-usual state of affairs. The recession brought with it a higher urgency for the development of what-if models in order to understand the future and build the capacity for predicting and creating redundancies in the face of change and adversity. The use of operational information can help banks chart out an appropriate course of action for the future. The recession also changed the banking regulatory frameworks across the world in ways that banks either have to respond to operationally or comply with. For instance, the 2008 case of the Reserve Bank of India and the ban of 19 retail banks three years later is a perfect example. In Kenya, the central bank passed regulations necessitating the use of computerized information systems for the validation of internal or external applications to check for any inconsistencies (CBK, 2013). Banks also have to respond to potential changes in regulatory frameworks. For instance, if interest rates are deregulated, they must adjust technique accordingly (ICreate, 2015). 3.5 Business Intelligence in Modern Marketing The dynamism of customer needs, preferences and ability with regards to the banking sector continues to highlight the importance of the use of business intelligence in shaping modern marketing campaigns. In the dynamic world, banks must communicate with customers promptly and through the most effective channels. Analytics will be important in tracking product performance to determine the most effective channels through which to push products (Cognizant, 2011). Business intelligence also plays an important role in navigating the field of social media. Not many banks have reached the right comfort level with social media. The number of bank users and potential customers that spend time on social media means that banks can no longer ignore this platform. The few that have jumped into this sector are already reaping the benefits. Customers on social media generate a large amount of chatter that can be useful in helping gain specific insights into their preferences. Social media analytics can help banks gain an insight into what the customers want, which in turn will help in improvements and enhancements. Business intelligence is not only about the organizational processes and the employee behavior. A focus on customer-related analytics, especially in the retail banking sector, is a key source of competitive advantage (Cognizant, 2011). Digitalization started out as an option but is now a necessity in the strategies of most banks (Deloitte, 2014). As more banks look to exploit consumer-related data, success will depend on how well the bank converts this data into insights. Information gathered must be converted into useful information as quickly as possible. 3.6 Outsourcing The adoption of new technologies and gathering of information is not new to banks. However, IT infrastructures are under immense pressure to change. Business intelligence has widespread applications in the operations of banks. It is important that data and analytics become an important aspect of retail bank strategy. Using business intelligence tactically and strategically requires the banks to find relevant data. The pressure on banks is immense because data mining platforms are moving from legacy mainframe-based systems to service-oriented architecture. For banks, this means not only upgrading their legacy systems but also the integration of data across the different business units and banking locations. This results in an evening out of the data and information quality across the organization, and a single version of the truth. 4.0 Conclusion Effective and powerful banking transactions have to base on information systems. As such, effective business transactions that complement to the current business environment have to find a lasting solution to various challenges that hinder quality service delivery. The present market demands necessitates for a competitive and exemplary service provision in various financial institutions. Essentially, application of BI in banking will enable various banks to remain competitive across the globe. The BI has evolved in the past decade and has significantly improved service provision in various financial institutions.BI systems auto-initiate actions and commands that are sent to it by various clients. Essentially, the systems have greatly improved service delivery rate to a large number of customers seeking banking services. Consequently, banks can handle various market demands appropriately based on current business environment. Various BI components provide banks with varied avenues that help in presenting current market situation. As a result, risks, challenges and fear of losing data do not affect banks. Evidently, banks who have effectively implemented the BI system in their financial transactions realize maximum output. Additionally, their clients are satisfied since the system prioritizes customer needs. BI helps in maintaining high competition among other financial institutions offering banking services. As such, quality service is ensured by various banks. In the current world, competition is only one click away. Customers change preferences regularly, and new products enter the market with almost as much frequency. For businesses to stay competitive, it is important for them to be able to sense and respond to these changes quickly and accurately. Technology enables banking corporations to gather huge amounts of data from customer transactions and employee behavior. Such data can easily be turned into information for decision-making support (Wanda, 2014). The process of collection of data and tools for the improvement of the organization’s processes is the core of business intelligence (Turban, et al., 2014). Given the nature of banks, they possess information that few other industries can match. However, no two banks possess the same type of data strictly. Modern banks have to respond to such challenges as automation of processes, aggressive competition and increased expectation from customers, acquisition and mergers, and new product development (Ubiparipović & Đurković, 2011). The benefits of business intelligence are often more than what is evident at first sight (Hočevar & Jaklič, 2010). There are those effects that can be measured, either directly or indirectly. Business intelligence, however, also has effects that are difficult to measure and some that cannot be measured, such as the unpredictable benefits that can only be revealed by using business intelligence for a long time. Business intelligence improves support for administrative decisions. This means investments in technology must be aligned to the objectives of the organization. On the other hand, this technological investment must help the organization achieve its objectives. Investment in business intelligence information technology must incur some intangible costs. Evaluating the cost of this installation and implementation of business intelligence might seem easier than the evaluation of the benefits. Although there might be challenges and difficulties, cost evaluation is much more straightforward than the evaluation of benefits of business intelligence, especially in the banking sector. The common questions when evaluating benefits are the overall costs of data sources and intellectual capital, how to evaluate the resultant time savings and whether or not to take into account the opportunity cost. Having highlighted the need for business intelligence in the banking sector, evaluated the benefits and suggested critical success factors, the verdict is that despite the difficulties in measuring the result, the banking sector must use business intelligence actively to stay competitive. The sector continues to recognize the benefits of business intelligence, a fact that has resulted in several implications. A typical example of the potential of business intelligence, its benefits, and the implications lies in the story of the Reserve Bank of India. In 1998, it appointed a committee that it tasked with the upgrade of technology in the banking sector. The main task of the committee was the creation of better data mining and warehousing systems, through which the sector players could develop more efficient management information systems. The results of the work of this committee were that banks began implementing better systems for customer relations management, monitoring risk, and performance. Fast forward to 2011, and the RBI penalized several banks for non-compliance with instructions from the recommendations of the 2008 committee. Some of the conditions included failures to carry out due diligence on the suitability of products, lack of verification of underlying limits and sale of products to users without risk management policies. Although the committee highlighted the need and importance of business intelligence, it raised several questions regarding the tools necessary for banks to zero in on effective information, business insights and strategies to drive performance (ICreate, 2015). This highlights the need for the banking sector to take into careful consideration the following implications of the knowledge of business intelligence. Banks may, and often do have all the right data or data mining channels. However, it takes the expert judgment to identify relevant data points and how they may be used. This, combined with the sheer magnitude of potential data points and cost considerations is pushing many banks towards partnerships and outsourcing when searching for talent. 5.0 Reference List Adelman, S. Moss, L. &Barbusinski, L. (2013). “I found several definitions of BI,' DM Review. International Business Journal vol. 6 pp 45 Bogdan, U. & Emina, D. (2015). Application of Business Intelligence in the Banking Industry. Accessed from http://www.ef.uns.ac.rs/mis/archive-pdf/2011%20-%20No4/MIS2011_4_4.pdf [on 4th August 2015] CBK, 2013. Banking Sector Records Improved Performance. [Online] Available at: . [Accessed 4 August 2015]. Cognizant, 2011. How Analytics Can Transform. [Online] Available at: http://www.cognizant.com/InsightsWhitepapers/How-Analytics-Can-Transform-the-U.S.-Retail-Banking-Sector.pdf[Accessed 4 August 2015]. Cohen, M. (2014). Exploiting Response Models – Optimizing Cross-Sell and Up-Sell Opportunities in Banking. Information Systems 29, 327-341, 2003 Elsevier Ltd Curt Hall. (2013). Data Warehousing for Business Intelligence. Accessed fromhttp://www.cutter.com/itreports/RP68E.pdf on [4th August 2014] Davenport, T.H. (2013). Process Innovation: Reengineering Work through Information Technology. Harvard Business School Press, Boston. Deloitte, 2014. Digital Transaction Banking: Opportunities & Challenges. [Online] Available at: . [Accessed 4 August 2015]. Goebel, M. & Le, G. (2014). A survey of data mining and knowledge discovery software tools. Volume 1, Issue 1 Publisher ACM New York, NY, USA . Golfarelli M., Rizzi S., &Cella L. (2014). Beyond Data Warehousing: What’s next in Business Intelligence? Proceedings of DOLAP-04 Hanseth, O. & Lyytinen, K., 2010. Design theory for dynamic complexity in information infrastructures: the case of building internet. Journal of Information Technology, Volume 25, pp. 1-19. Henfridsson, O. & Bygstad, B., 2013. The Generative Mechanisms of Digital Infrastructure Evolution. MIS Quarterly, 37(3), pp. 907-931. Hočevar, B. & Jaklič, J., 2010. Assessing the Benefits of Business Intelligence Systems: A Case Study. Management, 15(1), pp. 87- 119. ICreate, 2015. Business Intelligence in Banks. [Online] Available at: . [Accessed 4 August 2015]. Inmon, W.H. (2013) Building the Operational Data Store’, Wiley Publishers-New York, 2nd edition. Jonathan, W. (2013) Business Intelligence: “What is Business Intelligence?” DM Business Review Kamara, D., 2014. Strategic Value of Business Intelligence Systems, Nairobi: University of Nairobi. Lee, J.H. &Park, S.C. (2015). Intelligent Profitable Customers’ Segmentation System Based on Business Intelligence Tools. Expert Systems with Applications Journal 29, 145-152 Malhotra, Y. (2013) ‘information management to knowledge management: Beyond “Hi-Tech Hidebound” systems.” Knowledge Management Journal Mosimann, R. & Connelly, R. (2014).The Performance Manager for Banking. Harvard Business Review Nadeem, M. &Jffri, H.A. S. (2015).Application of Business Intelligence in Banks. Accessed from . [on 4th August 2015] Ranjan, J. (2015). Business Intelligence: Concepts, Components, Techniques and Benefits. Journal of Theoretical and Applied InformationTechnology Simon, D. (2013). Customer Value: Gaining the competitive Agent. Harvard Business Review Stackowiak, R., Rayman, J. & Greenwald, R. (2014). Oracle Data Warehousing and Business Intelligence Solutions. Wiley Publishing, Inc, Indianapolis Thierauf, R. J., 2001. Effective Business Intelligence Systems. 1st ed. Westport: Quorum Books. Tim, K. (2013), Business Intelligence for Intelligent Business. DM Business Review Turban, E. &McLean, E. (2013). Information Technology for Management. Making Connections for Strategic Advantage, 2nd Edition Turban, E., Sharda, R. & Delen, D., 2014. Decision Support and Business Intelligence Systems, Pearson New International Edition. Tvrdikova, M. (2013). Support of Decision Making by Business Intelligence Tools’, Computer Information Systems and Industrial Management Applications. 6thInternational Conference, pp. 368. Ubiparipović, B. & Đurković, E., 2011. Application of Business Intelligence in the Banking Industry. Management Information Systems, 6(4), pp. 23- 30. Wanda, P., 2014. Breakfast at Tiffany's: The Study of a SUccessful Business Intelligence Solution as an Information Infrastructure, Oslo: Norwegian School of IT. Zeng, L., Xu, L., Shi, Z., Wang, M. & Wu, W. (2014). Techniques, Process, And Enterprise Solutions Of Business Intelligence. 2006 IEEE Conference on Systems, Man, and Cybernetics, Taipei, Taiwan, Vol. 6, pp. 4722 Read More
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