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Question: Pick a System or Technology which could be developed in-house or outsourced or a combination of the two approaches. Make arguments and provide supporting rationale for outsourcing or no outsourcing or a hybrid approach. You may wish to provide a table of Advantages and Disadvantages and then provide rationale for your decision. Answer: Data warehouse concept In recent past it was consideration as a big problem in order to give the access to the important information to the people of the enterprise in a timely manner and when they actually needed it. (Arnott, Lizama Song, 2017). The concept of the data warehouse may be considered as a federal repository taking into account the data of the enterprise which is collected by various system of businesses. The main aim of the report is to take into consideration the concept of the data warehouse and the concept of it being outsourced. In order to explain the concept, the advantage and the disadvantage related to the outsourcing is taken into account. Concept of outsourcing The concept of outsourcing is majorly becoming a method which is preferred of doing the business by the companies for varied reasons (Trieu, V. H Burton-Jones, 2017). The important aspects of outsourcing are reduction in the cost related to operation, improvement of the focus of the company, accelerating reengineering benefits and so on. In recent times companies have focused towards the concept of outsourcing the technology than any other functions related to the business (Mohammed, 2016). Framework of data warehouse As the concept of the data warehouse has gradually increased many organisation has accepted their viability. One of the reason that can be associated with the concept of the data warehouse taking so much time to evolve is due to the factor that the technology is very much comprehensive. There are many details aspects which have to be taken into consideration before its direct implementation. In order to get a clear view point of the process of data warehousing emerged it is very much essential to have the data warehouse architecture (Golfarelli, Rizzi Cella, 2016). Architecture of data warehouse The structure of the data, presentation and the concept of processing that mainly exist for the user who are termed as end user within the framework of enterprise represents the architecture related to the data warehouse. There are a number of interconnected parts that make up the architecture they are: Information access layer External data base layer Data access layer Data directory layer Process management layer Application messaging layer Data warehouse layer Data staging layer (Foster Godbole, 2016). There are mainly two approaches of the data warehouse, mainly bottom up and top down. The top down approach that spins the data mart for a specific group of users after the complete data of the warehouse has been created (Watson Wixom, 2016). On the other hand, the bottom up process approach build the data marts first and then mainly combines the process into a single, compressed data warehouse. A data warehouse is mainly housed on an enterprise serve mainframe or increasingly in the concept of the cloud. The data from a various transaction which are online processing (OLTP) applications and other major sources is selectively extracted for the use by the analytical application and the query of the user (Golfarelli, Rizzi Cella, 2016). Advantage of Data warehouse outsourcing The advantage which are related to the data warehouse are as follows: Shipping cost: one of the major advantage which is related to then data warehousing and the fulfilment of the process is the ability to tap into the concept of the shipping account related to the courier network. When the combination is done of the throughput of a number of ecommerce business into the prospective of one account then these economics of the scale can be very much passed on to the individual business. This may result in significant cost saving (Watson Wixom, 2016). Flexibility: when the company owns and manages their own warehouse then the flexibility which can be achieved can be in the field of cost reduction as well as the reduction in the staff that has to be employed. Dispatching order: when the outsourcing concept is involved in the operation and the integration with the processing system, it can be very much assured that highest efficiency can be achieved from it. The system can allow orders being picked up, packed and dispatched all the time even during the weekends (Davis, Aggarwal Baskin, 2016). Disadvantage of Data warehouse outsourcing The disadvantage which are related to the data warehouse are as follows: Control: when the concept of the outsourcing is applied to any field of business, it can directly involve lack of control over the process. the company would not have any sight over the item or the data as they are being controlled or executed by a third party. Data protection: ones the overall concept is moved or outsourced the protection field lies on the hand of the third party. The company does not have any control over the data. It directly involves that the overall working is in the hand of the third party as well as the security. This may lead to a big problem (Fazal et al., 2017). Associated cost The cost of implementation can run from anywhere from $40000 to $3 million (Vercellis, 2017). This cost is directly dependent on the factor of the size of the carriers and the number of the customers who are involved in the business. Taking into account todays global competition, business is desperately trying to boost or on the other hand at least maintain the profit as well as market share while reducing the overall cost related to it (Yeoh Popovi?, 2016). Conclusion There should always be a clear concept and understanding of the process which are related to the huge amount of data within the infrastructure of any organisation. in order to manage the overall data there would be a huge demand of the IT/IS staff. In order to remove the stated problem outsourcing can be considered as an alternative in order to achieve the result. The burden which is involved in the overall working is left over to the third party and the burden is directly removed from the organisation. References Arnott, D., Lizama, F., Song, Y. (2017). Patterns of business intelligence systems use in organizations. Decision Support Systems, 97, 58-68. Fazal, T., Strutt, D., Gibb, R., Armstrong, M., Adendorff, M., Helal, R. (2017). U.S. Patent No. 9,740,992. Washington, DC: U.S. Patent and Trademark Office. Foster, E. C., Godbole, S. (2016). Data Warehousing. In Database Systems (pp. 377-390). Apress. Mohammed, M. A. (2016). Improving the Efficiency of BI Report Generation for Data Warehousing Projects. Vercellis, C. (2017). Business intelligence: data mining and optimization for decision making. John Wiley Sons. Watson, H. J., Wixom, B. H. (2016). The current state of business intelligence. Computer, 40(9). Yeoh, W., Popovi?, A. (2016). Extending the understanding of critical success factors for implementing business intelligence systems. Journal of the Association for Information Science and Technology, 67(1), 134-147. Golfarelli, M., Rizzi, S., Cella, I. (2016, November). Beyond data warehousing: what's next in business intelligence?. In Proceedings of the 7th ACM international workshop on Data warehousing and OLAP (pp. 1-6). ACM. Davis, K. C., Aggarwal, D., Baskin, S. (2016, December). Scaling Data Warehousing Course Projects. In Computational Science and Computational Intelligence (CSCI), 2016 International Conference on (pp. 241-245). IEEE. Trieu, V. H., Burton-Jones, A. (2017, January). A Model of the Production of Representational Fidelity: Insights from the Business Intelligence Systems Context. In Academy of Management Proceedings (Vol. 2017, No. 1, p. 13316). Academy of Management.