Enterprises uses data warehouse to store and fetch all information related to the company. The data warehouse is used by small and large enterprises. The small businesses use lightweight and chap hardware and software to provide online data analysis. The traditional OLAP architecture is storage costly and cumbersome. The data warehouse has therefore become an important component of modern decision support system. Both large and small businesses collect large amount of details and are sensitive with business intelligence.
The small businesses are significant on a national, global and local basis. Despite immense advantages, the existing DSSs in most cases remain insufficient to small business. The accessibility is dimmed y several factors such as complexity for more employees, irrelevant functionality, high price, high requirements for a hardware infrastructure, and low flexibility to handle a vigorously changing dynamic business environment.
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The paper provides a view on how technologies surveyed can be enhanced to work in SME’s business intelligent. The survey includes analyses on web-powered business intelligence. Web is the best platform for delivery of business applications for both large and small enterprises. Web warehouse use data derived from the Web. On the other hand, we get the concentration of web technologies in data warehousing ( Rauch et al., 2018 ). Web-data warehouse buys several characteristics from traditional data warehouse. The Web warehouse differs from the DW technology. The web browsers offer various advantages over traditional warehouse. These advantages include decrease of system training time, and low cost of maintenance and deployment. The web warehouse is divided into classes. These include XML data ware-houses and XML document warehouse.
The Web, memory, and vector BI solutions are characterized with numerous advantages and disadvantages. The three services represent the overall system. Joint together, the services provide unlimited advantages to the business. However, the three services are related to a few disadvantages. These advantages and disadvantages vary from one situation to the other and therefore, they can be compared.
The services help in saving money. However, the charge fees change from one server to the other. In most cases, the price of the service dictates the reliability of the services. The hundreds of insurers offering different prices allow the customers to select the cheapest option. In this case, the small businesses are able to save. However, the cheapest services are characterized with low quality services.
The BI solutions aimed at large-scale enterprises are irrelevant to small and middle-scale businesses. The large-scale businesses are characterized with large amount of information. In this case, the data needs a large memory. The condition of situation has limited middle and small-scale business from adopting the solutions. These factors include complexity for most users, high price and high requirements for a hardware infrastructure.
High price
The overall setup of the system includes different services and labor. The business requires to establish different infrastructures and warehouse to incorporate the entire system. on the other hand, the system is meant to receive regular maintenance and update. The competitive level of the system requires a deep and strong foundation. Therefore, the business should be in a position to finance all the activities. In this case, the small and middle-class business are unable to raise such huge costs.
High requirements for a hardware infrastructure
The system includes some well coded software compatible with the current situation. The software should be able to update regularly without too much of struggle. However, the firm is required to purchase and develop different infrastructures requires a mega finance ( Gudfinnsson, Rose & Aggestam, 2019 ). The requirements for the hardware infrastructure are hard to surpass hence discouraging the small firms. In most cases, the small firms are unable to reach the standards of hardware infrastructure.
Complexity for most users
The system is developed in business to serve both the clients and the employees. The employees should be in possession of quality skills and experience with the system. lack of knowledge will cause several issues related to the usage. The huge companies are able to poach and hire qualified employees. However, the small businesses are unable to access employees with such high knowledge. The small businesses are mainly forced to seek some of these services from certified cloud computing services. In this case, they are able to access services at an affordable price.
Web and memory-based BI are different solutions but they share several characteristics. The two solutions merge business intelligence and data warehousing with web or memory-based technology. The services offer simplicity and cheapness of browser use and installation. The systems are easy to use ( Eremeeva, Volkova, & Khamidulina, 2018 ). The knowledge required is regarde d nontechnical. Unlike other systems, the skills demanded are general and every user can efficiently acquire within a short period of training. The services have an ability to eliminate problems acquired by the operating system. The solutions are well structured to diagnose all problems affecting the operating system. In other instances, the solutions detect any kind of malfunction and make a quick diagnosis. Lastly, the solutions are able to command some simple updates depending on the current software used.
References
Eremeeva, E. A., Volkova, N. V., & Khamidulina, A. M. (2018). Public Support for Small and Medium-Sized Business in the Regions of the Russian Federation. AD ALTA-JOURNAL OF INTERDISCIPLINARY RESEARCH , 8 (1), 40-43.
Gudfinnsson, K., Rose, J., & Aggestam, L. (2019). Tackling Lack of Motivation in Aspirational Analytics Companies: SME Examples from the Manufacturing Industry. International Journal of Business Intelligence Research (IJBIR) , 10 (1), 1-18.
Rauch, E., Matt, D. T., Brown, C. A., Towner, W., Vickery, A., & Santiteerakul, S. (2018). Transfer of Industry 4.0 to Small and Medium Sized Enterprises. Advances in Transdisciplinary Engineering , 7 , 63-71.
