Business intelligence is play an important tool in communication and decision-making. This also helps in targeting different types of audiences such as marketers, accountants, product managers, salespeople, and finance professionals. Business Intelligence is designed with the help of SAS. This is a comprehensive guide to utilizing the power of SAS software to create and implement sophisticated business intelligence solutions. The SAS is to assemble and organize data, design and implement data models, and create interactive visualizations. Additionally, SAS provides advice to develop and deploy a business intelligence strategy that aligns with organizational objectives. With the help of this SAS, business users can become more adept at leveraging the power to create, deliver, and maintain a successful business intelligence system.
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The Orion star analyst of the business intelligence department starts work the get access to the SAS Viya. Where different information is provided on the process of the Orion star product report. The data is help in access and investigation (Saha, 2022). This also helps in understanding the data set that involves the sharp as well as the issue's possible data. The data that is analyzed is related to the customer order id and quantity, where the descriptive analysis is determined.
The above figure 1 shows the mean, median as well as mode value of the customer id, customer types, street ID, and street number. Where the Average customer id, customer types, street ID, and street number are 12485.22, 1505.58, 6099067349.75, and 855.88 respectively (Bansal and Kumar, 20200. The minimum customer id, customer types, street ID, and street number are 4, 1020, 1600100760, and 1 respectively. The maximum customer id, customer types, street ID, and street numbers are 70221, 3010, 9260129395, and 9658 respectively.
Figure 2: Descriptive analysis of customers
The above figure 2 shows the descriptive analysis of the customers. Where the std. Deviation, (1811.21), Std. error (206.41), variance (3280475.92), total observations (77), and so on (Bhat, 2020). These are the descriptive analysis that describes the statistical value of the different customer with respect to order id and street. ;
Figure 3 shows the frequency of the customer type ID. Where the maximum frequency is found in 1000 order type IDs and the least frequency is found in 2500 above customer type IDs. ;
Figure 4: Customers' order quantity
Figure 4 represents the customer order quantity. Where the minimum quantity is 1, the maximum quantity is 6, the average quantity is 1.93 and the sum of the quantity is 285. ;
Figure 5: Descriptive analysis of customer orders quantity
Figure 5 shows the descriptive analysis of the customer order quantity. Where the different customer orders quantity std. Deviation (1.01), Std. error (0.08), variance (1.02), total observations (148), and so on (Agustiono, 2019). These are the descriptive analysis that describes the statistical value of the different customer with respect to order quantity. ;
Figure 6: Frequency of customer orders quantity
Figure 6 shows the frequency of customer order quantity. The frequency of the customer is depend on the quantity. In the figure, the highest quantity frequency is 1 and the least quantity frequency is 6. ;
Table 1: Report of Frequency percent and quantity with customer and product
The above table 1, shows the report frequency percent and quantity with the customers and the product . This report includes the supplier, total retails, frequency percentage as well as quantity. Where the different customers purchase their products from different suppliers and the total retail prices that they spent on their products. There is also analyze the frequency of the purchase of the customer's products. This report helps business intelligence managers to manage their stock of products.
Table 2: Frequency with a product category
The above table shows the frequency of the product category. Where the different types of products are purchased by the suppliers. Where the highest frequency product is clothes and the lowest category product is swim sports. ;
Figure 7: Frequency of supplier country
The above figure shows the frequency of suppliers' countries. Where the higher supplier country is the US and the lower supplier country is FR.
Figure 8: Frequency of salary
The above figure shows the frequency of salary. Where the higher frequency salary is 50000 and the lower frequency salary is 25000. ;
3.0 Part B
3.1 Business Case
The business intelligence of the department of retails, auditing, and marketing company with their new client is the world’s largest toy manufacturer with the operations. Before some weeks the company had appointed a new director of marketing who announce a strategy for the best-selling of the product (Olszak, 2020). Where the manager uses the SAS software for the analysis with the help of graphs.
3.2 Discuss
Figure 9: Minimum, maximum, and average birth date, employee ID, salary, etc
The above figure shows the minimum, maximum, and average of the Birth date, employee ID, hire date, and salary. The average of the Birth date, employee ID, hire date, and salary are 3622.58, 120713.90, 12054.28, and 31160.12 respectively. ;
Figure 10: Descriptive analysis of Birth date, employee ID, hire date, and salary
The above figure shows the descriptive analysis of Birth date, employee ID, hire date, and salary. Where the std. Deviation (5456.29), Std. error (424.77), variance (29771126.33), total observations (165), and so on (Gilliland et al., 2021). This analysis is help in determining the relation between the birth date, employee ID, hire date, and salary of the people. ;
Figure 11: Frequency of Birth date
The above figure shows the frequency of the birth date. Where the higher frequency is 8000 and the lower frequency is -3000. ;
Conclusion
The above analysis is based on the SAS software. This software is used by the sales managers to determine the actual sales and improve the strategy of the sales. So that the company could improve its sales and analyze the pReferences of the customer regarding its product. This software helps in analyzing the market and the sales of the product. ;
Reference list
Books
Deckler, G., 2019. ;Learn Power BI: A beginner's guide to developing interactive business intelligence solutions using Microsoft Power BI. Packt Publishing Ltd.
Gilliland, M., Tashman, L. and Sglavo, U., 2021. ;Business forecasting: the emerging role of artificial intelligence and machine learning. John Wiley & Sons.
Madonsela, N.S., 2020. ;The application of a business intelligence tool for service delivery improvement: The case of South Africa. University of Johannesburg (South Africa).
Olszak, C.M., 2020. ;Business intelligence and big data: Drivers of organizational success. CRC press.
Journals
Agustiono, W., 2019. Academic business intelligence: can a small and medium-sized University Afford to build and deploy it within limited resources. ;J. Inf. Syst. Eng. Bus. Intell, ;5(1).
ARGHIR, D.C., Ioana-Gilia, D.U.?.A. and Onu??, M., 2019. Organizational development through business intelligence and data mining. ;Database Systems Journal, ;10(1), pp.82-99.
Bansal, S. and Kumar, A., 2020. Competitive advantage: intelligent way of doing business. ;International Journal of Public Sector Performance Management, ;6(2), pp.278-285.
Berhil, S., Benlahmar, H. and Labani, N., 2020. A review paper on artificial intelligence at the service of human resources management. ;Indonesian Journal of Electrical Engineering and Computer Science, ;18(1), pp.32-40.
Bhat, H.J., 2020. Investigate the Implication of “Self-service Business Intelligence (SSBI)”—A Big Data Trend in Today’s Business World. ;Curr. Trends Inf. Technol, ;10, pp.17-22.
El Morr, C., Ali-Hassan, H., El Morr, C. and Ali-Hassan, H., 2019. Healthcare, data analytics, and business intelligence. ;Analytics in healthcare: a practical introduction, pp.1-13.
Lokaadinugroho, I., Girsang, A.S. and Burhanudin, B., 2021. Tableau Business Intelligence Using the 9 Steps of Kimball’s Data Warehouse & Extract Transform Loading of the Pentaho Data Integration Process Approach in Higher Education. ;Engineering, MAthematics and Computer Science (EMACS) Journal, ;3(1), pp.1-11.
Saabith, A., Vinothraj, T. and Fareez, M., 2022. Business Intelligence Tools;Systematic Review. ;International Journal of Research in Engineering and Science (IJRES). www. ijres. org, ;10(10), pp.394-408.
Saeed, K., Sidorova, A. and Vasanthan, A., 2022. The Bundling of Business Intelligence and Analytics. ;Journal of Computer Information Systems, pp.1-12.
Saha, J., 2022. Analytics in Indian Businesses: Marketing Perspective. ;Indian Business@ 75: Research on Trends and Prospects, p.215.
Yiu, L.D., Yeung, A.C. and Jong, A.P., 2020. Business intelligence systems and operational capability: an empirical analysis of high-tech sectors. ;Industrial Management & Data Systems, ;120(6), pp.1195-1215.
Website
sas.com, 2023, SAS Business solution Business Intelligence Insights | SAS India:, Available at:https://www.sas.com/en_in/solutions/business-intelligence.html [Accessed On: 7.3.2023]
